High sensitivity movement disorder treatment device or system

ABSTRACT

The present invention relates to a movement disorder monitor with high sensitivity, and a method of measuring the severity of a subject&#39;s movement disorder. The present invention additionally relates to a drug delivery system for dosing a subject in response to the increased severity of a subject&#39;s symptoms. The present invention provides for a system and method, which can accurately and repeatably quantify symptoms of movements disorders, accurately quantifies symptoms utilizing both kinetic information and/or electromyography (EMG) data, that can be worn continuously to provide continuous information to be analyzed as needed by the clinician, that can provide analysis in real-time, that allows for home monitoring of symptoms in subject&#39;s with these movement disorders to capture the complex fluctuation patterns of the disease over the course of days, weeks or months, that maximizes subject safety, and that provides substantially real-time remote access to data by the clinician or physician.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of co-pending U.S. patent applicationSer. No. 13/784,939, filed on Mar. 5, 2013, which was acontinuation-n-part of U.S. patent application Ser. No. 13/455,423,which was filed on Apr. 25, 2012 and which was a continuation of U.S.patent application Ser. No. 11/082,668 which was filed on Mar. 17, 2005,and which issued as U.S. Pat. No. 8,187,209 on May 29, 2012.

The U.S. Government has a paid-up license in this invention and theright in limited circumstances to require the patent owner to licenseothers on reasonable terms provided for by the terms of grant numbers1R43NS043816-01A1, 2R44NS043816-02/03 1R43NS074627, 7R43NS065554, and2R44MD004049, awarded by the National Institutes of Health.

BACKGROUND OF THE INVENTION 1. Field of the Invention

The present invention relates to a movement disorder monitor, and amethod of measuring and quantifying the severity of a subject's movementdisorder and symptoms thereof. The present invention additionallyrelates to a development system, and a treatment and drug deliverysystem for dosing a subject in response to changes in severity of asubject's symptoms.

2. Technical Background

Movement disorders include, but are not limited to, Parkinson's disease(PD), essential tremor, dystonia, and Tourette's syndrome. Suchdisorders present a multitude of symptoms affecting a person's dailylife, those symptoms include tremor, bradykinesia, rigidity,gait/balance disturbances, dyskinesias, and the like. The treatments caninvolve pharmaceutical interventions, fetal cell transplants, surgery,or deep brain stimulation in some of these disorders. The efficacy ofthese interventions is often judged by the intervention's ability toalleviate subject symptoms and improve their quality of life. WithParkinson's disease for example, the major symptoms that affect qualityof life are tremor, bradykinesia, rigidity, and dyskinesia. Thesesymptoms are partly responsible for the subject's functional disabilityand social embarrassment.

Tremors are involuntary muscle contractions characterized byoscillations of a body part. Tremor of the hands can be cosmeticallyupsetting and affect functional tasks such as grasping of objects.Resting tremors usually occur at frequencies of approximately 4-7 Hzwhile the frequency of action of postural tremor is higher, usuallybetween 9-11 Hz. Tremor is a symptom often targeted by treatment. Thestandard clinical method for analyzing rest and postural or actiontremor is qualitative assessment by a clinician and assignment of ascore.

Bradykinesia refers to delays or hesitations in initiating movements andslowness in executing movements. The standard clinical method foranalyzing bradykinesia is qualitative assessment by a clinician andassignment of a score. This score is assigned while the subjectcompletes a repetitive finger-tapping task, a repetitive handopening-closing task, and a pronation-supination task. Objectiveassessment by this means is difficult and variable. It has been foundthat movement rate and time are useful in better characterizingbradykinesia.

Rigidity occurs because muscles of the body are overly excited. Theneurons involved in inhibition circuitry have died due to Parkinson'sdisease and muscles may receive continuous excitation. Rigidity causesthe joints of the subject to become stiff and decreases range of motion.During normal movement, an agonist muscle contracts while the antagonistmuscles relax. However, due to the constant motor unit input, theantagonist is unable to relax. Again, the standard clinical method foranalyzing rigidity is qualitative assessment by a clinician andassignment of a score. To do so a clinician passively moves thesubject's joints through a range of motion while the subject relaxes.

Dyskinesia is one of the most common and disabling complications ofchronic drug therapy. Dyskinesias are wild involuntary movements thattypically occur when the benefit from the drug therapy is at itsmaximum. Clinical assessment of dyskinesias typically relies onself-reporting by the subject. There is a great need to objectivelyquantify these involuntary movements in view of the growing number ofpharmacologic agents and surgical procedures to improve dyskinesia.

While standard clinical evaluation involves qualitative assessment ofthese symptoms, recently some efforts have been made to quantifysymptoms of movement disorders. Accelerometers and gyroscopes have beenused individually to quantify some of these movement disorder symptoms,however, alone each sensor has limitations. Accelerometers operate inresponse to the local gravitational field; therefore they often haveproblems in separating changes in linear acceleration from rotation.Further, results of a second integration required to obtain linearposition are often contaminated with noise, making measurement difficultat best. Gyroscopes measure angular velocity independent of gravity witha good frequency response; however, static angular position cannot bemeasured accurately due to DC drift characteristic with these devices.Combining the information from both accelerometers and gyroscopes canprovide a more accurate method of quantifying motion.

With the tremendous amount of research into neuroprotective treatmentsdesigned to slow the progression of movement disorders, and particularlyParkinson's disease, the need for standardized, highly sensitiveassessments of movement disorder treatments cannot be understated.Large-scale clinical drug trials for medication and drug treatmentmethods often involve dozens of sites and thousands of subjects locatedall over the world. Outcome measures are typically in the form of asingle clinical assessment completed at weekly or monthly intervals.These clinical assessments can suffer from bias, placebo effects,limited resolution, and poor intra- and inter-rater reliability.

Currently, no commercially available system provides a means toobjectively quantify the severity of movement disorder symptoms inreal-time. Furthermore, many of these systems are bulky and cannoteasily be worn by a subject during normal daily activities so as aresult can only be used to monitor the subject in an intermittentfashion. In addition, some of these systems are tethered, which reducessubject safety, limits home monitoring capabilities, and does not allowfor recording of some movement disorder symptoms. Finally, none of thecurrent systems have clinician interface software, which quantifiessymptoms such as tremor, bradykinesia, rigidity, and dyskinesias andrelates them to standard rating scales such as the Unified Parkinson'sDisease Rating Scale (UPDRS). Additionally, none of these systems haveclinical video instruction and real-time clinical video feedback.

Even further, the currently available systems are typically hindered bya large degree of variability in the quantification of symptom severity.This is due in large part to the subjective nature of scoring systems,such as the UPDRS, which require clinician observation of the subjectand/or movement data, and/or subject feedback regarding their subjectiveevaluation of the severity of symptoms. Systems requiring subjectfeedback, for example by use of a journal for recording the subject'sperception of symptoms throughout the day, suffer from a lack of subjectcompliance. Many subjects provide skewed information, or more often failto comply with the reporting standards completely and then fill in thejournal near to the time of an appointment with the clinician, ratherthan on a daily basis as the symptoms occur (or do not occur). Evensystems which rely in part or completely on scoring of clinicians orother trained personnel offer a high degree of variability due to theneed for subjective observation or reporting of the severity ofsymptoms. Different clinicians might score a given observationdifferently, and the same clinician might score the same observationdifferently if presented with the data at different times. Thisvariability and subjectivity can prevent an accurate quantification ofsymptom severity which may lead to inappropriate treatment of thesubject including under or over medication. This variability andsubjectivity further hinders the research and development processrequiring long periods of time and large numbers of subjects in order toverify and qualify new treatment methods for clinical use.

Measurement errors can take the form of inconsistencies caused by theparticipant's physical or mental condition, variations in the testingprocedure, or to tester error. Additionally, subjects may perform betteror more consistent on a task due to learning effects rather than as aresult of the therapy being studied. Various methods to improveconsistency such as using the same rater or testing on the same time ofday can improve reliability; however, most of these techniques are notpractical for large, multi-center clinical trials.

As an example, the most common outcome measure in Parkinson's Diseasedrug trials, the motor section of the Unified Parkinson's Disease RatingScale (UPDRS Section III), requires a clinician to qualitatively ratevarious motor symptoms on a 0-4 integer scale while viewing the subjectperforming tasks. While studies have shown relative high test-retestreliability for the UPDRS-III as a whole (see e.g., Teresa Steffen etal, Test-Retest Reliability and Minimal Detectable Change on Balance andAmbulation Tests, the 36-Item Short-Form Health Survey, and the UnifiedParkinson Disease Rating Scale in People with Parkinsonism, 88 PHYSICALTHERAPY 733 (Jun. 1, 2008)), this traditional method of subjectevaluation presents several problems for large scale pharmaceuticalstudies. The required presence of a trained clinician to rate symptomscreates costs associated with subject travel and clinician time. Inaddition, the use of medications for treatment of Parkinson's Diseaseoften causes symptom fluctuations during the day, which cannot bemonitored during a single visit with the trained clinician. Tocompensate for this lack of temporal resolution, subjects are oftenasked to complete daily diaries; however, in clinical trials, thesediaries are notoriously poor in quality as subjects may have a tendencyto wait and fill out the diaries in retrospect rather than throughoutthe day on a daily basis. Also, clinical trials typically employ severalclinicians at different sites, which may lead to symptom scoringvariability and in turn decreased sensitivity due to the subjectiveobservations of each clinician. Finally, the discrete nature of theinteger scores (0, 1, 2, 3, or 4) under the UPDRS does not allow for thehigh sensitivity measurements that would be necessary to capture thevery subtle changes that might occur during a neuroprotective drugtrial. Neuroprotective drugs target subjects with early Parkinson'sDisease when symptoms are still very mild (correlating to a 0 or 1 scoreon the UPDRS). Evaluation of neuroprotective therapies can take years oreven decades due to the long period before a UPDRS measurable responseis seen.

Many researchers have cited the inability to measure slight changes inmotor symptom severity using the UPDRS as a hurdle in evaluatingpotential neuroprotective agents. And while reliability of the UPDRS-III(the motor section) as a whole may be high, specific symptoms or items,such as those related to bradykinesia for example, lack specificity andsuffer from poor intra- and inter-rater reliability. For rating tremor,the Movement Disorders Society (MDS) revision of the UPDRS tremorscoring guidelines specify amplitude ranges in centimeters thatcorrespond to a 0-4 score (see C. G. Goetz et al., Movement DisorderSociety-sponsored revision of the Unified Parkinson's Disease RatingScale (MDS-UPDRS): scale presentation and clinimetric testing results.,23 MOV. DISORD. 2129 (Nov. 15, 2008)); however, it is difficult, if notimpossible, to judge tremor amplitude precisely by visual observationalone. Even if precise visual observations were possible, converting awide range of amplitudes to an integer score greatly reduces resolution.For evaluating finger tapping, hand movements, and pronation-supination,evaluations are even less reliable since raters must account for speed,amplitude, rhythm, hesitations, freezing, and fatigue, all with a singlescore. In a study designed to test inter-rater reliability, the UPDRSfinger tapping task, the most widely used measure of bradykinesia, wasmisclassified by 70.6% of the 54.6% of clinicians who failed their firstrating (see C. G. Goetz and G. T. Stebbins, Assuring interraterreliability for the UPDRS motor section: utility of the UPDRS teachingtape. 19 MOV. DISORD. 1453 (2004)). As for intra-rater reliability, twostudies showed only poor to fair agreement in bradykinesia ratings (seeD. A. Bennett et al., Metric properties of nurses' ratings ofparkinsonian signs with a modified Unified Parkinson's Disease RatingScale, 49 Neurology 1580 (1997); see also R. Camicioli R et al.,Discriminating mild parkinsonism: Methods for epidemiological research.16 MOV. DISORD, 33 (2001)). A third study showed fair to good agreement;however, raters were not blinded and the subjects had early, untreatedPD, which restricts the range of test-retest reliability (see A.Siderowf et al., Test-retest reliability of the unified Parkinson'sdisease rating scale in patients with early Parkinson's disease: resultsfrom a multicenter clinical trial. 17 MOV. DISORD. 758 (2002)).Recently, the modified bradykinesia rating scale (MBRS) was introducedfor independently rating the bradykinesia manifestations of speed,amplitude, and rhythm. Each manifestation is given an integer score from0-4 during finger-tapping, hand movements, and pronation-supinationtasks. The MBRS has similar inter- and intra-rater reliability to thatof the UPDRS and was found to be more sensitive than the UPDRS inidentifying how different aspects of bradykinesia respond to medication,highlighting the need for more sensitive assessment of bradykinesia.While an improvement, the MBRS is still a subjective scale with limited(whole number: 0, 1, 2, 3, or 4) resolution, cannot be captured withouta clinician present, and has inter- and intra-rater reliability issuessimilar to the UPDRS (see D. A. Heldman D A et al, The modifiedbradykinesia rating scale for Parkinson's disease: Reliability andcomparison with kinematic measures, 26 MOV. DISORD. 1859 (2011).

It is therefore an object of the present invention to provide a systemfor accurately quantifying symptoms of movement disorders. It is stillanother object of the present invention to provide a system thataccurately quantifies symptoms utilizing both kinetic information, andin some embodiments electromyography (EMG) data. It is further an objectof the present invention to provide accurate, reliable, repeatablequantification of movement disorder symptoms allowing for reduced timeand cost in development, and more rapid and accurate treatment ofsubjects. It is still another object of the present invention to providea wireless movement disorder system that can be worn continuously toprovide continuous information to be analyzed as needed by theclinician, though need not be, and may preferably not be worncontinuously. It is still further another object of the presentinvention to provide a movement disorder system that can provideanalysis in real-time. It is a further object of the present inventionto provide a movement disorder symptom quantification system that canautomatically and immediately make data and the provided analyticalinformation available for further analysis and review in real-time. Itis still further another object of the present invention to provide amovement disorder system to allow for home monitoring of symptoms insubject's with these movement disorders to capture the complexfluctuation patterns of the disease over the course of days, weeks ormonths. It is still further an object of the present invention tomaximize subject safety. It is still further an object of the presentinvention to provide a system with clinical video instruction andreal-time clinical video feedback. It is still further an object of thepresent invention to provide a treatment delivery system that canmonitor symptoms in subject's and deliver treatment in response to thosesymptoms. Finally it is the object of the present invention to provideremote access to the clinician or physician.

SUMMARY OF THE INVENTION

The present invention relates to a movement disorder monitor, and amethod of measuring the severity of a subject's movement disorder. Thepresent invention additionally relates to a treatment delivery systemincluding drugs for treating or dosing a subject in response to changesin the severity of a subject's symptoms.

The present invention provides for a system and method, which canaccurately quantify symptoms of movements disorders, accuratelyquantifies symptoms utilizing both kinetic information and in someembodiments electromyography (EMG) data, that can be worn continuouslyto provide continuous information to be analyzed as needed by theclinician, that can provide analysis in real-time, that allows for homemonitoring of symptoms in subject's with these movement disorders tocapture the complex fluctuation patterns of the disease over the courseof days, weeks or months, that maximizes subject safety, and thatprovides remote access to the clinician or physician. One such system isdescribed in U.S. patent application Ser. No. 12/818,819, which isherein incorporated by reference.

In one embodiment, the present invention includes a portable movementdisorder device for measuring severity of a subject's movement disordercomprising a first sensor for measuring a subject's external body motionhaving a signal related to the external body motion; and a second sensorfor measuring a subject's electrical muscle activity wherein theseverity of the subject's movement disorder is calculated based in parton the signals of the first and second sensors.

In another embodiment, the present invention includes a method ofmeasuring severity of a subject's movement disorder comprising the stepsof measuring a subject's external body motion; transmitting wirelessly asignal based in part on the subject's measured external body motion;receiving the wirelessly transmitted signal; and scoring the severity ofa subject's movement disorder based in part on the wirelesslytransmitted signal.

In still another embodiment, the present invention includes a portablemovement disorder device or system for measuring severity of a subject'smovement disorder comprising at least one sensor having a signal formeasuring a subject's external body motion or physiological signalassociated with a movement disorder; at least one processor forreceiving the signal, and calculating the severity of the subject'smovement disorder in real time.

In still another embodiment, the present invention includes a portablemovement disorder device or system for measuring severity of a subject'smovement disorder comprising at least one sensor having a signal formeasuring a subject's external body motion or physiological signalassociated with a movement disorder; recording that data to memory onthe device, downloading that data to a computer at a later time andcalculating the severity of the subject's movement disorder.

In still another embodiment, the present invention includes a drugdelivery system comprising at least one sensor having a signal formeasuring a subject's external body motion or physiological signalassociated with a movement disorder; an actuator which allows amedication to be delivered from a reservoir external to the subject to apoint internal to the subject; and a closed-loop control system foractivating and deactivating the actuator based in part on the signalfrom the at least one sensor.

In yet another embodiment, the present invention includes a method ofquantifying severity of a subject's movement disorder comprising thesteps of providing a device to a subject, the device comprising at leastone sensor having a signal corresponding to a subject's external bodymotion associated with a movement disorder, measuring the subject'sexternal body motion with the at least one sensor while the subjectperforms at least one movement disorder test corresponding to at leastone movement disorder symptom, transmitting a signal from the at leastone sensor to a processor, and calculating substantially in real timewith the processor a symptom quantification measure based at least inpart on the signal from the at least one sensor, wherein the device hasa real-time average intraclass correlation (ICC) of at least about 0.60.

In still another embodiment, the present invention includes a method ofquantifying severity of a subject's movement disorder comprising thesteps of providing a device to a subject, the device comprising at leastone sensor having a signal corresponding to a subject's external bodymotion associated with a movement disorder, measuring the subject'sexternal body motion with the at least one sensor while the subjectperforms at least one movement disorder test corresponding to at leastone movement disorder symptom, transmitting a signal from the at leastone sensor to a processor, and calculating substantially in real timewith the processor a symptom quantification measure based at least inpart on the signal from the at least one sensor, wherein the device hasa real-time average minimum detectable change (MDC) that represents achange of about 25% or less of the total scale of the particular test.

In yet another embodiment, the present invention includes a method ofquantifying severity of a subject's movement disorder comprising thesteps of providing a device to a subject, the device comprising at leastone sensor having a signal corresponding to a subject's external bodymotion associated with a movement disorder, measuring the subject'sexternal body motion with the at least one sensor while the subjectperforms at least one first movement disorder test corresponding to atleast one movement disorder symptom, transmitting a first signal fromthe at least one sensor to a processor, calculating substantially inreal time with the processor a first symptom quantification measurebased at least in part on the first signal from the at least one sensor,measuring the subject's external body motion with the at least onesensor while the subject performs at least one second movement disordertest corresponding to at least one movement disorder symptom, the atleast one second movement disorder test being the same as the at leastone first movement disorder test, transmitting a second signal from theat least one sensor to a processor, and calculating substantially inreal time with the processor a second symptom quantification measurebased at least in part on the second signal from the at least onesensor, wherein the first and second symptom quantification measureshave an average intraclass correlation (ICC) of at least about 0.60.

In still another embodiment, the present invention includes a method ofquantifying severity of a subject's movement disorder comprising thesteps of providing a device to a subject, the device comprising at leastone sensor having a signal corresponding to a subject's external bodymotion associated with a movement disorder, measuring the subject'sexternal body motion with the at least one sensor while the subjectperforms at least one first movement disorder test corresponding to atleast one movement disorder symptom, transmitting a first signal fromthe at least one sensor to a processor, calculating substantially inreal time with the processor a first symptom quantification measurebased at least in part on the signal from the at least one sensor,measuring the subject's external body motion with the at least onesensor while the subject performs at least one second movement disordertest corresponding to at least one movement disorder symptom, the atleast one second movement disorder test being the same as the at leastone first movement disorder test, transmitting a second signal from theat least one sensor to a processor, and calculating substantially inreal time with the processor a second symptom quantification measurebased at least in part on the second signal from the at least onesensor, wherein the first and second symptom quantification measureshave an average minimal detectable change (MDC) that represents a changeof about 25% or less of the total scale of the particular test.

In yet another embodiment, the present invention includes a method ofquantifying severity of a subject's movement disorder comprising thesteps of providing a device to a subject, the device comprising at leastthree sensors, each having a signal corresponding to a subject'sexternal body motion associated with a movement disorder, measuring thesubject's external body motion with the at least three sensors while thesubject performs at least one first movement disorder test correspondingto at least one movement disorder symptom, transmitting first signalsfrom each of the at least three sensors to a processor, calculatingsubstantially in real time with the processor a first symptomquantification measure based at least in part on the first signals fromthe at least three sensors, measuring the subject's external body motionwith the at least three sensors while the subject performs at least onesecond movement disorder test corresponding to at least one movementdisorder symptom, the at least one second movement disorder test beingthe same as the at least one first movement disorder test, transmittingsecond signals from each of the at least three sensors to a processor,and calculating substantially in real time with the processor a secondsymptom quantification measure based at least in part on the secondsignals from the at least three sensors, wherein the first and secondsymptom quantification measures have an average intraclass correlation(ICC) of at least about 0.60.

In yet another embodiment, the present invention includes a method ofquantifying severity of a subject's movement disorder comprising thesteps of providing a device to a subject, the device comprising at leastone sensor having a signal corresponding to a subject's external bodymotion associated with a movement disorder, measuring the subject'sexternal body motion with the at least one sensor while the subjectperforms at least two first movement disorder tests, the at least twotests belonging to a symptom group corresponding to the subject's motorexamination, transmitting a first signal from the at least one sensor toa processor, calculating substantially in real time with the processor afirst motor examination symptom quantification measure based at least inpart on the first signal from the at least one sensor, measuring thesubject's external body motion with the at least one sensor while thesubject performs at least two second movement disorder tests, the atleast two tests belonging to a symptom group corresponding to thesubject's motor examination, the at least two second movement disordertests being the same as the at least two first movement disorder tests,transmitting a second signal from the at least one sensor to aprocessor, and calculating substantially in real time with the processora second motor examination symptom quantification measure based at leastin part on the second signal from the at least one sensor, wherein thefirst and second motor examination symptom quantification measures havean average intraclass correlation (ICC) of at least about 0.60.

In yet another embodiment, the present invention includes a method ofquantifying severity of a subject's movement disorder comprising thesteps of providing a device to a subject, the device comprising at leastone sensor having a signal corresponding to a subject's external bodymotion associated with a movement disorder, measuring the subject'sexternal body motion with the at least one sensor while the subjectperforms at least two first movement disorder tests, the at least twotests belonging to a symptom group corresponding to the subject's motorexamination, transmitting a first signal from the at least one sensor toa processor, calculating substantially in real time with the processor afirst motor examination symptom quantification measure based at least inpart on the first signal from the at least one sensor, measuring thesubject's external body motion with the at least one sensor while thesubject performs at least two second movement disorder tests, the atleast two tests belonging to a symptom group corresponding to thesubject's motor examination, the at least two second movement disordertests being the same as the at least two first movement disorder tests,transmitting a second signal from the at least one sensor to aprocessor, and calculating substantially in real time with the processora second motor examination symptom quantification measure based at leastin part on the second signal from the at least one sensor, wherein thefirst and second motor examination symptom quantification measures havean average minimum detectable change (MDC) that represents a change ofabout 25% or less of the total scale of the particular test.

In still another embodiment, the present invention includes a method ofquantifying severity of a subject's movement disorder comprising thesteps of providing a device to a subject, the device comprising at leastone sensor having a signal corresponding to a subject's external bodymotion associated with a movement disorder, measuring the subject'sexternal body motion with the at least one sensor while the subjectperforms at least three first movement disorder tests, the at leastthree first tests belonging to a symptom group corresponding to thesubject's motor examination, transmitting a first signal from the atleast one sensor to a processor, calculating substantially in real timewith the processor a first motor examination symptom quantificationmeasure for each of the at least three first tests, each measure basedat least in part on the first signal from the at least one sensor,creating a first total symptom quantification measure by combining thethree first symptom quantification measures, measuring the subject'sexternal body motion with the at least one sensor while the subjectperforms at least three second movement disorder tests, the at leastthree second tests belonging to a symptom group corresponding to thesubject's motor examination, the at least three second movement disordertests being the same as the at least three first movement disordertests, transmitting a second signal from the at least one sensor to aprocessor, calculating substantially in real time with the processor asecond motor examination symptom quantification measure for each of theat least three second tests, each measure based at least in part on thesecond signal from the at least one sensor, creating a second totalsymptom quantification measure by combining the three second symptomquantification measures, wherein the first and second total symptomquantification measures have an average minimum detectable change (MDC)that represents a change of about 25% or less of the total scale of theparticular test.

In still yet another embodiment, the present invention includes a methodof quantifying severity of a subject's movement disorder comprising thesteps of providing a device to a subject, the device comprising at leastthree sensors, each having a signal corresponding to a subject'sexternal body motion associated with a movement disorder, measuring thesubject's external body motion with the at least three sensors while thesubject performs at least one first movement disorder test correspondingto at least one movement disorder symptom, transmitting first signalsfrom each of the at least three sensors to a processor, calculatingsubstantially in real time with the processor a first symptomquantification measure based at least in part on the first signals fromthe at least three sensors, measuring the subject's external body motionwith the at least three sensors while the subject performs at least onesecond movement disorder test corresponding to at least one movementdisorder symptom, the at least one second movement disorder test beingthe same as the at least one first movement disorder test, transmittingsecond signals from each of the at least three sensors to a processor,and calculating substantially in real time with the processor a secondsymptom quantification measure based at least in part on the secondsignals from the at least three sensors, wherein the first and secondsymptom quantification measures have an average minimal detectablechange (MDC) that represents a change of about 25% or less of the totalscale of the particular test.

In still yet another embodiment, the present invention includes aportable device for quantifying severity of a subject's movementdisorder comprising at least one sensor having a signal for measuring asubject's external body motion or physiological signal associated with amovement disorder, and at least one processor for receiving the sensorsignal and calculating the severity of the subject's movement disordersymptom(s) in real time, wherein the device has a real-time averageintraclass correlation (ICC) of at least about 0.60.

In yet still another embodiment, the present invention includes aportable device for quantifying severity of a subject's movementdisorder comprising at least one sensor having a signal for measuring asubject's external body motion or physiological signal associated with amovement disorder, and at least one processor for receiving the sensorsignal and calculating the severity of the subject's movement disordersymptom(s) in real time, wherein the device has a real-time averageminimum detectable change (MIX) that represents a change of about 25% orless of the total scale of a particular test.

In yet another embodiment, the present invention includes a portabledevice for quantifying severity of a subject's movement disordercomprising a first sensor for measuring a subject's external body motionhaving a signal related to the subject's external body motion, and asecond sensor for measuring a subject's electrical muscle activityhaving a signal related to the subject's electrical muscle activity,wherein the severity of the subject's movement disorder is calculatedbased in part on the signals of the first and second sensors, andwherein subsequent measurements of movement disorder severity result inan intraclass correlation of at least about 0.60.

In still another embodiment, the present invention includes a portabledevice for quantifying severity of a subject's movement disordercomprising a first sensor for measuring a subject's external body motionhaving a signal related to the subject's external body motion, and asecond sensor for measuring a subject's electrical muscle activityhaving a signal related to the subject's electrical muscle activity,wherein the severity of the subject's movement disorder is calculatedbased in part on the signals of the first and second sensors, andwherein subsequent measurements of movement disorder severity result ina minimum detectable change (MDC) that represents a change of about 25%or less of the total scale of a particular test.

In still yet another embodiment, the present invention includes aportable device for quantifying severity of a subject's movementdisorder comprising at least one external sensor having a signal formeasuring a subject's external body motion or physiological signalassociated with a movement disorder, and at least one processor forreceiving the signal, and calculating the severity of the subject'smovement disorder in real time, wherein subsequent measurements ofmovement disorder severity result in an intraclass correlation of atleast about 0.60.

In yet still another embodiment, the present invention includes aportable device for quantifying severity of a subject's movementdisorder comprising at least one external sensor having a signal formeasuring a subject's external body motion or physiological signalassociated with a movement disorder, and at least one processor forreceiving the signal, and calculating the severity of the subject'smovement disorder in real time, wherein subsequent measurements ofmovement disorder severity result in a minimum detectable change (MDC)that represents a change of about 25% or less of the total scale of aparticular test.

Additional features and advantages of the invention will be set forth inthe detailed description which follows, and in part will be readilyapparent to those skilled in the art from that description or recognizedby practicing the invention as described herein, including the detaileddescription which follows, the claims, as well as the appended drawings.

It is to be understood that both the foregoing general description andthe following detailed description are merely exemplary of theinvention, and are intended to provide an overview or framework forunderstanding the nature and character of the invention as it isclaimed. The accompanying drawings are included to provide a furtherunderstanding of the invention, and are incorporated in and constitute apart of this specification. The drawings illustrate various embodimentsof the invention; and together with the description serve to explain theprinciples and operation of the invention.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1. Electrical schematic of a gyroscope useful in the presentinvention.

FIG. 2. Electrical schematic of a dual axis accelerometer useful in thepresent invention.

FIG. 3. Electrical schematic of a single axis accelerometer useful inthe present invention.

FIGS. 4a-4c . Electronic Schematic of the Subject Worn sensor boardunit.

FIG. 5. Electronic Schematic of the Subject Worn transceiver moduleunit.

FIGS. 5a-5i . Exploded views of various sections of the ElectronicSchematic of the Subject Worn transceiver module unit.

FIG. 6. Schematic showing placement of various components of themovement disorder device with an external sensor module for the hand andEMG electrodes.

FIG. 7. Schematic showing various system components of the movementdisorder device.

FIG. 8. Flow diagram of system in continuous operating mode.

FIG. 9. Flow diagram of system in task operating mode.

FIG. 10. Flow diagram of system in a combination operating mode.

FIG. 11. Flow diagram for one embodiment of the software used in thepresent invention.

FIG. 12. Flow diagram for one embodiment of a closed-loop drug deliverysystem of the present invention.

FIG. 13. Schematic showing placement of various components of closedloop drug delivery system with an implantable reservoir.

FIG. 14. Schematic showing placement of various components of closedloop drug delivery system with an external reservoir to transcutaneousdelivery.

FIG. 15. Flow diagram of a sensitive method for quantifying movementdisorder symptom severity comprising a set of at least one test that isrepeated, where sensitivity is measured by intraclass correlation (ICC)of repeated tests.

FIG. 16. Flow diagram of a sensitive method for quantifying movementdisorder symptom severity comprising a set of at least one test that isrepeated, where sensitivity is measured by minimal detectable change(MDC).

FIG. 17. Flow diagram of another embodiment of a sensitive method forquantifying movement disorder symptom severity with a device comprisingat least three sensors, the method comprising a set of at least one testthat is repeated, and where sensitivity is measured by intraclasscorrelation (CC) of repeated tests.

FIG. 18. Flow diagram of another embodiment of a sensitive method forquantifying movement disorder symptom severity with a device comprisingat least three sensors, the method comprising a set of at least one testthat is repeated, and where sensitivity is measured by minimumdetectable change (MDC) of repeated tests.

FIG. 19 Flow diagram of a sensitive method for quantifying movementdisorder symptom severity comprising a set of at least two tests, bothtests corresponding to the same grouping or classification of symptoms,wherein the set of at least two tests is repeated, and where sensitivityis measured by intraclass correlation (ICC) of repeated tests.

FIG. 20. Flow diagram of another embodiment of a sensitive method forquantifying movement disorder symptom severity comprising a set of atleast three tests, each of the at least three tests corresponding to adifferent group or classification of symptoms, wherein the set of atleast three tests are repeated, and where sensitivity is measured byintraclass correlation (ICC).

FIG. 21. Flow diagram of a sensitive method for quantifying movementdisorder symptom severity comprising a set of at least two tests, bothtests corresponding to the same grouping or classification of symptoms,wherein the set of at least two tests is repeated, and where sensitivityis measured by minimum detectable change (MDC) of repeated tests.

FIG. 22. Flow diagram of another embodiment of a sensitive method forquantifying movement disorder symptom severity comprising a set of atleast three tests, each of the at least three tests corresponding to adifferent group or classification of symptoms, wherein the set of atleast three tests are repeated, and where sensitivity is measured byminimum detectable change (MDC).

FIG. 23. Electrical schematic/block diagram of alternative sensor unitcomprising a 3-axis accelerometer and a 3-axis gyroscope.

FIG. 24. Block diagram depicting electronic components of one embodimentof the present invention of a subject worn sensor unit for measuring thesubject's external body movements and quantifying the severity ofmovement disorder symptoms.

FIG. 25. Block diagram depicting data movement and availability betweenthe device and end users.

DESCRIPTION OF THE PREFERRED EMBODIMENT

The present invention relates to a movement disorder monitor, and amethod of measuring the severity of a subject's movement disorder. Thepresent invention additionally relates to a drug delivery system fordosing a subject in response to the increased severity of a subject'ssymptoms.

The devices, systems and methods of the various embodiments of thepresent invention are used to analyze, score, and treat various movementdisorders. Movement disorders for purposes of this application includebut are not limited to Parkinson's disease (PD) and essential tremor.Some of the treatments used for these disorders involve pharmaceuticalinterventions, fetal cell transplants, surgery, or deep brainstimulation. The efficacy of these interventions is often judged by theinterventions ability to alleviate subject symptoms and improve theirquality of life. The subject on which the devices, system or method isused is a human or other form of animal.

The devices of the various embodiments of the present invention arepreferably portable. By portable it is meant among other things that thedevice is capable of being transported relatively easily. Relative easyin transport means that the device can be carried by a single person,generally in a carrying case to the point of use or application.Furthermore the device preferably should be relatively light-weight. Byrelatively light-weight, preferably the device weighs less than about 3lbs., more preferably less than about 2 lbs., even more preferably lessthan about 1 lb., and most preferably less than about 0.5 lbs. By beinglight-weight and further compact, the device should gain greateracceptance for use by the subject. The system for measuring andcalculating the severity of the symptoms including external computerspreferably weighs less than about 15 lbs., more preferably less thanabout 10 lbs., and most preferably less than about 5 lbs. This systemmore preferably can fit in a reasonably sized carrying case so thesubject or their caregiver can easily transport the system.

Another advantage of the systems and methods of the present invention isthe ability to determine or calculate the severity of a subject'ssymptoms in real time, which may be measured or quantified by providinga symptom quantification measure or score. By real time it is meant thatwithin 30 minutes the severity of a subject's symptoms can be calculatedor determined. Preferably, the subject's symptoms can be calculated ordetermined in less than about 1 minute, more preferably in less thanabout 30 seconds, still more preferably in less than about 15 seconds,yet more preferably in less than about 10 seconds, even more preferablyin less than about 5 seconds, yet still more preferably in less thanabout 1 second, even still more preferably in less than about 0.1seconds, and most preferably in less than about 0.01 seconds.

The devices of the various embodiments of the present invention can formpart of a system for use by a physician, veterinarian, technician orclinician for analysis or evaluation of a subject's movement disorder;for pharmaceutical research; or for delivery of pharmaceuticalcompounds. Other elements of this system may include but are not limitedto receivers, routers, communication devices, processors, displays, drugdelivery devices and the like, some of which are described further invarious embodiments described in more detail below.

Various embodiments of the present invention may include a sensor formeasuring a subject's external body motion. Many types of sensors areknown by those skilled in the art for measuring external body motion.These sensors include but are not limited to accelerometers, gyroscopes,magnetometers, resistive bend sensors, force sensors, combinationsthereof, and the like. Preferably, a combination using at least anaccelerometer and gyroscope is used. FIG. 1 is an electrical schematicdiagram for one embodiment of a gyroscope 8 used as a sensor or in asensor of the present invention. The sensor element 10 functions on theprinciple of the Coriolis Effect and a capacitive-based sensing system.Rotation of the sensor 10 causes a shift in response of an oscillatingsilicon structure resulting in a change in capacitance. An applicationspecific integrated circuit (ASIC) 14, using a standard complementarymetal oxide semiconductor (CMOS) manufacturing process, detects andtransforms changes in capacitance into an analog output voltage 16,which is proportional to angular rate. The sensor element designutilizes differential capacitors and symmetry to significantly reduceerrors from acceleration and off-axis rotations.

FIG. 2 is an electrical schematic diagram for one embodiment of a dualaxis accelerometer of the present invention. The dual axis accelerationmeasurement system 30 is on a single monolithic IC. They contain apolysilicon surface-micromachined sensor and signal conditioningcircuitry to implement an open-loop acceleration measurementarchitecture. For each axis 32, 34 an output circuit converts the analogsignal to a duty cycle modulated (DCM) digital signal that can bedecoded with a counter/timer port 36 on a microprocessor. The dual axisaccelerometer is capable of measuring both positive and negativeaccelerations. The sensor 30 is a surface micromachined polysiliconstructure built on top of the silicon wafer. Polysilicon springs suspendthe structure over the surface of the wafer and provide a resistanceagainst acceleration forces. Deflection of the structure is measuredusing a differential capacitor that consists of independent fixed platesand central plates attached to the moving mass. The fixed plates aredriven by 180-degree out of phase square waves. Acceleration willdeflect the beam and unbalance the differential capacitor, resulting inan output square wave whose amplitude is proportional to acceleration.Phase sensitive demodulation techniques are then used to rectify thesignal and determine the direction of the acceleration. The output ofthe demodulator 33, 35 drives a duty cycle modulator (DCM) 37 stagethrough a 32 kOhm resistor 38. At this point a pin is available on eachchannel to allow the user to set the signal bandwidth of the device byadding a capacitor. This filtering improves measurement resolution andhelps prevent aliasing. After being low-pass filtered, the analog signalis converted to a duty cycle modulated signal by the DCM stage 37. Asingle resistor sets the period for a complete cycle (T2). A 0 gacceleration produces a nominally 50% duty cycle. The accelerationsignal can be determined by measuring the length of the T1 and T2 pulseswith a counter/timer or with a polling loop using a low costmicrocontroller.

FIG. 3 is an electrical schematic diagram for one embodiment of a singleaxis accelerometer of the present invention. The accelerometer 20 isfabricated using a surface micro-machining process. The fabricationtechnique uses standard integrated circuit manufacturing methodsenabling all signal processing circuitry to be combined on the same chipwith the sensor 22. The surface micro-machined sensor element 22 is madeby depositing polysilicon on a sacrificial oxide layer that is thenetched away leaving a suspended sensor element. A differential capacitorsensor is composed of fixed plates and moving plates attached to thebeam that moves in response to acceleration. Movement of the beamchanges the differential capacitance, which is measured by the on chipcircuitry. All the circuitry 24 needed to drive the sensor and convertthe capacitance change to voltage is incorporated on the chip requiringno external components except for standard power supply decoupling. Bothsensitivity and the zero-g value are ratiometric to the supply voltage,so that ratiometric devices following the accelerometer (such as ananalog to digital converter (ADC), etc.) will track the accelerometer ifthe supply voltage changes. The output voltage (VOUT) 26 is a functionof both the acceleration input and the power supply voltage (VS).

FIGS. 4a-4c illustrate an electrical schematic diagram for oneembodiment of the subject worn sensor unit. FIG. 4a shows a kineticsensor board 50 (or subject worn external sensor) of the presentinvention. The kinetic sensor board 50 is preferably configured withboth an accelerometer and a gyroscope for quantifying the subject'smotion. In this particular embodiment, the kinetic sensor board 50consists of three gyroscopes 51 and three orthogonal accelerometers 52.The kinetic sensor board also includes a microprocessor (TexasInstruments mSP430-169) and a power interface section.

FIG. 5 is an electrical schematic diagram for one embodiment of thesubject worn transceiver module 64. Exploded views of various sectionsof the electrical schematic diagram are shown in FIGS. 5a-5i . Thetransceiver module includes a blue tooth radio (EB100 A7 Engineering) toprovide wireless communications with the subject PC, EMG amplifier anddata acquisition circuitry, on board memory, a microprocessor 70, FIGS.5 and 5 f, (Analog Devices ADVC7020), and a battery power supply(lithium powered) 66, FIG. 5i that supplies power to both thetransceiver module 64, FIG. 5h , and one or more external sensor modules50. The transceiver module also includes a USB port to provide batteryrecharging and serial communications with the subject PC. Thetransceiver module also includes a push button input. The transceivermodule also includes a limo connector to attached EMG electrode leads tothe module.

FIG. 6 illustrates one possible embodiment of the subject 55 worncomponents of the system combining the sensor board 50 and thetransceiver module 64. The sensor board 50 is worn on the subject's 55finger 51 and the transceiver module 64 is worn on the subject's 55wrist 63. The transceiver module 64 and one or more external sensormodules 50 are connected by a thin multi-wire leads 54. The transceivermodule 64 in this embodiment connects to one or more electrodes 60 usedto measure EMG.

FIG. 7 illustrates one embodiment of the system components of thewireless movement disorder monitor. The external sensor module 50 inthis embodiment contains three orthogonal accelerometers (not shown) andthree orthogonal gyroscopes (not shown). This input to the externalsensor module 50 consists of the kinetic forces applied by the user andmeasured by the accelerometers and gyroscopes. The output from the boardis linear acceleration and angular velocity data in the form of outputvoltages. These output voltages are input to the transceiver module 64.These voltages undergo signal conditioning and filtering before samplingby an analog to digital converter. This digital data is then stored inon board memory and/or transmitted as a packet in RF transmission by ablue tooth transceiver. Additionally, EMG electrodes 60 worn by thesubject may be input to the transceiver module. An amplifier on thetransceiver module 64 amplifies the EMG signal(s) before signalconditioning, filtering, and sampling by the analog to digitalconverter. The EMG data is also stored in the on board memory and/orcontained in the packet for RE transmission. A microprocessor (notshown) in the transceiver module 64 controls the entire process. Kineticand EMG data packets may be sent by RF transmission to a nearby computertransceiver 72 which receives the data using an embedded blue toothradio to a computer 76. Kinetic and EMG data may also be stored on theon board memory and downloaded to a computer 76 at a later time. Thecomputer 76 then processes, analyzes, and stores the data. The kineticsensor board 50 measures accelerations along and angular velocitiesabout each of three orthogonal axes. The signals from the accelerometersand gyroscopes of the kinetic sensor board 50 are preferably input intoa processor for signal conditioning and filtering. Preferably, threeAnalog Devices gyroscopes (ADXRS300) were utilized on the kinetic sensorboard with an input range up to 1200 degrees/second. The Analog Devicesparts were selected after an analysis of cost, size and powerconsumption. The ball grid array type of component was selected tominimize size. Additionally, a MEMS technology dual axis accelerometer,from Analog Devices (ADXL210), was employed to record accelerationsalong the x and y-axes. The sensors provide 80 dB dynamic range, lownoise (1 mg/sqrt (Hz)), and low power (<2 mA per axis) in a surfacemount package. Other combinations of accelerometers and gyroscopes knownto those skilled in the art could also be used. A lightweight plastichousing was then used to house the sensor for measuring the subject'sexternal body motion. The external body motion sensor(s) can be worn onthe subject's finger, hand, wrist, fore arm, upper arm, head, chest,back, legs, feet and/or toes.

Various embodiments of the present invention may include a sensor(s) formeasuring the subject's electrical muscle activity through techniquessuch as electromyography (EMG) or the like. FIG. 7 shows the EMGelectrodes 60 which are connected to an amplifier 62. With an EMGsensor, a voltage difference or difference in electrical potential ismeasured between at least two recording electrodes. The electrodes usedcan be any type known to those skilled in the art including bothindwelling (needle), surface and dry electrodes. Typical EMG electrodesconnections may have an impedance in the range of from 5 to 10 K ohms.It is in general desirable to reduce such impedance levels to below 2 Kohms. Therefore a conductive paste or gel may be applied to theelectrode to create a connection with an impedance below 2 K ohms.Alternatively, the subject(s) skin may be mechanically abraded, theelectrode may be amplified or a dry electrode may be used. Dryphysiological recording electrodes of the type described in U.S. patentapplication Ser. No. 09/949,055 are herein incorporated by reference.Dry electrodes provide the advantage that there is no gel to dry out andno skin to abrade or clean. Additionally if electrodes are used as thesensor(s), preferably at least three electrodes are used—two signalelectrodes and one reference electrode.

Preferably, the transceiver module 64 contains one or more electroniccomponents such as the microprocessor 70 for detecting both the signalsfrom the gyroscopes 51 and accelerometers 52, and for detecting thesignal from EMG electrode 60. Preferably, the one or more electroniccomponents also filter (and possibly amplify) the detected EMG signalsand kinetic motion signals, and more preferably convert these signals,which are in an analog form into a digital signal for transmission tothe remote receiving unit. The one or more electronic components areattached to the subject as part of device or system. Further preferably,the one or more electronic components can receive a signal from theremote receiving unit or other remote transmitters. The one or moreelectronic components may include circuitry for but are not limited tofor example electrode amplifiers, signal filters, analog to digitalconverter, blue tooth radio, a DC power source and combinations thereof.The one or more electronic components may comprise one processing chip,multiple chips, single function components or combinations thereof,which can perform all of the necessary functions of detecting a kineticor physiological signal from the electrode, storing that data to memory,uploading data to a computer through a serial link, transmitting asignal corresponding to a kinetic or physiological signal to a receivingunit and optionally receiving a signal from a remote transmitter. Theseone or more electronic components can be assembled on a printed circuitboard or by any other means known to those skilled in the art.Preferably, the one or more electronic components can be assembled on aprinted circuit board or by other means so its imprint covers an arealess than 4 in², more preferably less than 2 in², even more preferablyless than 1 in², still even more preferably less than 0.5 in², and mostpreferably less than 0.25 in².

Preferably, the circuitry of the one or more electronic components isappropriately modified so as to function with any suitable miniature DCpower source. More preferably, the DC power source is a battery. Themost preferred battery of the present invention is lithium poweredbatteries. Lithium ion batteries offer high specific energy (the numberof given hours for a specific weight), which is preferable.Additionally, these commercially available batteries are readilyavailable and inexpensive. Other types of batteries include but are notlimited to primary and secondary batteries. Primary batteries are notrechargeable since the chemical reaction that produces the electricityis not reversible. Primary batteries include lithium primary batteries(e.g., lithium/thionyl chloride, lithium/manganese dioxide,lithium/carbon monofluoride, lithium/copper oxide, lithium/iodine,lithium/silver vanadium oxide and others), alkaline primary batteries,zinc-carbon, zinc chloride, magnesium/manganese dioxide,alkaline-manganese dioxide, mercuric oxide, silver oxide as well aszinc/air and others. Rechargeable (secondary) batteries includenickel-cadmium, nickel-zinc, nickel-metal hydride, rechargeablezinc/alkaline/manganese dioxide, lithium/polymer, lithium-ion andothers.

In some preferred embodiments, the system is capable of inductivecharging whereby an electromagnetic field is used to transfer energyfrom a charging mat or pad to the device. Preferably in suchembodiments, the charging mat or pad comprises and induction coil thatis used to create an alternating electromagnetic field. When the device,also comprising an induction coil, is placed on the charging mat or pad,the devices induction coil draws power from the electromagnetic fieldcreated by the charging mat's or pad's induction coil. The device's thenconverts this drawn power from electromagnet field energy intoelectrical current and uses this electrical current to charge thedevice's battery.

Preferably, the circuitry of the one or more electronic componentscomprises data acquisition circuitry further including an amplifier thatamplifies the EMG, (The gyroscope and accelerometer signals will notneed to be amplified.). The data acquisition circuitry is designed withthe goal of reducing size, lowering (or filtering) the noise, increasingthe DC offset rejection and reducing the system's offset voltages. Thedata acquisition circuitry may be constrained by the requirements forextremely high input impedance, very low noise and rejection of verylarge DC offset and common-mode voltages, while measuring a very smallsignal of interest. Additional constraints arise from the need for a“brick-wall” style input protection against ESD and EMI. The exactparameters of the design, such as input impedance, gain and passband,can be adjusted at the time of manufacture to suit a specificapplication via a table of component values to achieve a specificfull-scale range and passband.

More preferably, a low-noise, lower power instrumentation amplifier isused. The inputs for this circuitry is guarded with preferably, externalESD/EMI protection, and very high-impedance passive filters to reject DCcommon-mode and normal-mode voltages. Still preferably, theinstrumentation amplifier gain can be adjusted from unity toapproximately 100 to suit the requirements of a specific application. Ifadditional gain is required, it preferably is provided in a second-orderanti-bias filter, whose cutoff frequency can be adjusted to suit aspecific application, with due regard to the sampling rate. Stillpreferably, the reference input of the instrumentation amplifier istightly controlled by a DC cancellation integrator servo that usesclosed-loop control to cancel all DC offsets in the components in theanalog signal chain to within a few analog-to digital converter (ADC)counts of perfection, to ensure long term stability of the zeroreference.

Preferably, the signals are converted to a digital form. This can beachieved with an electronic component or processing chip through the useof an ADC. More preferably, the ADC restricts resolution to 16-bits dueto the ambient noise environment in such chips. Despite this constraint,the ADC remains the preferable method of choice for size-constrainedapplications such as with the present invention unless a custom dataacquisition chip is used because the integration reduces the total chipcount and significantly reduces the number of interconnects required onthe printed circuit board.

Preferably, the circuitry of the sensor board comprises a digitalsection. More preferably, the heart of the digital section of the sensorboard is the Texas Instruments MSP430-169 microcontroller. The TexasInstruments MSP430-169 microcontroller contains sufficient data andprogram memory, as well as peripherals which allow the entire digitalsection to be neatly bundled into a single carefully programmedprocessing chip. Still preferably, the onboard counter/timer sectionsare used to produce the data acquisition timer.

Preferably, the circuitry of the transceiver module comprises a digitalsection. More preferably, the heart of the digital section of the sensorboard is the Analog Devices ADVC7020 microcontroller. The Analog DevicesADVC7020 microcontroller contains sufficient data and program memory, aswell as peripherals which allow the entire digital section to be neatlybundled into a single carefully programmed processing chip. Stillpreferably, the onboard counter/timer sections are used to produce thedata acquisition timer.

Preferably, the circuitry for the one or more electronic components isdesigned to provide for communication with external quality control testequipment prior to sale, and more preferably with automated final testequipment. In order to supply such capability without impacting thefinal size of the finished unit, one embodiment is to design acommunications interface on a separate PCB using the SPI bus with anexternal UART and level-conversion circuitry to implement a standardserial interface for connection to a personal computer or some otherform of test equipment. The physical connection to such a devicerequires significant PCB area, so preferably the physical connection isdesigned to keep the PCB at minimal imprint area. More preferably, thephysical connection is designed with a break-off tab with fingers thatmate with an edge connector. This allows all required final testing andcalibration, including the programming of the processing chip memory,can be carried out through this connector, with test signals beingapplied to the analog inputs through the normal connections which remainaccessible in the final unit. By using an edge fingers on the productionunit, and an edge connector in the production testing and calibrationadapter, the system can be tested and calibrated without leaving anyunnecessary electronic components or too large an PCB imprint area onthe final unit.

Preferably, the circuitry for the one or more electronic componentscomprises nonvolatile, rewriteable memory. Alternatively, if thecircuitry for the one or more electronic components doesn't comprisenonvolatile, rewriteable memory then an approach should be used to allowfor reprogramming of the final parameters such as radio channelizationand data acquisition and scaling. Without nonvolatile, rewriteablememory, the program memory can be programmed only once. Therefore oneembodiment of the present invention involves selective programming of aspecific area of the program memory without programming the entirememory in one operation. Preferably, this is accomplished by settingaside a specific area of program memory large enough to store severalcopies of the required parameters. Procedurally, this is accomplished byinitially programming the circuitry for the one or more electroniccomponents with default parameters appropriate for the testing andcalibration. When the final parameters have been determined, the nextarea is programmed with these parameters. If the final testing andcalibration reveals problems, or some other need arises to change thevalues, additional variations of the parameters may be programmed. Thefirmware of various embodiments of the present invention scans for thefirst blank configuration block and then uses the value from thepreceding block as the operational parameters. This arrangement allowsfor reprogramming of the parameters up to several dozen times, with nosize penalty for external EEPROM or other nonvolatile RAM. The circuitryfor the one or more electronic components has provisions for in-circuitprogramming and verification of the program memory, and this issupported by the breakoff test connector. The operational parameters canthus be changed up until the time at which the test connector is brokenoff just before shipping the final unit. Thus the manufacturability andsize of the circuitry for the one or more electronic components isoptimized.

Preferably the circuitry of the one or more electronic componentsincludes an RF transmitter. Still preferably includes a blue tooth radiosystem utilizing the EB100 component from A7 engineering. Anotherfeature of the circuitry of the one or more electronic componentspreferably is an antenna. The antenna, preferably, is integrated in therest of the circuitry. The antenna can be configured in a number ofways, for example as a single loop, dipole, dipole with terminationimpedance, logarithmic-periodic, dielectric, strip conduction orreflector antenna. The antenna is designed to include but not be limitedto the best combination of usable range, production efficiency andend-system usability. Preferably, the antenna consists of one or moreconductive wires or strips, which are arranged in a pattern to maximizesurface area. The large surface area will allow for lower transmissionoutputs for the data transmission. The large surface area will also behelpful in receiving high frequency energy from an external power sourcefor storage. Optionally, the radio transmissions of the presentinvention may use frequency-selective antennas for separating thetransmission and receiving bands, if a RF transmitter and receiver areused on the electrode patch, and polarization-sensitive antennas inconnection with directional transmission. Polarization-sensitiveantennas consist of, for example, thin metal strips arranged in parallelon an insulating carrier material. Such a structure is insensitive to orpermeable to electromagnetic waves with vertical polarization; waveswith parallel polarization are reflected or absorbed depending on thedesign. It is possible to obtain in this way, for example good crosspolarization decoupling in connection with linear polarization. It isfurther possible to integrate the antenna into the frame of a processingchip or into one or more of the other electronic components, whereby theantenna is preferably realized by means of thin film technology. Theantenna can serve to just transfer data or for both transferring data toand for receiving control data received from a remote communicationstation which can include but is not limited to a wireless relay, acomputer or a processor system. Optionally, the antenna can also serveto receive high-frequency energy (for energy supply or supplement). Inany scenario, only one antenna is required for transmitting data,receiving data and optionally receiving energy. Optionally, directionalcouples can be arranged on the transmitter outputs of the electrodepatch and/or the remote communication station. The couplers being usedto measure the radiated or reflected radio wave transmission output. Anydamage to the antenna (or also any faulty adaptation) thus can beregistered, because it is expressed by increased reflection values.

An additional feature of the present invention is an optionalidentification unit. By allocating identification codes—a subject code,the remote communication station is capable of receiving andtransmitting data to several subjects, and for evaluating the data ifthe remote communication station is capable of doing so. This isrealized in a way such that the identification unit has control logic,as well as a memory for storing the identification codes. Theidentification unit is preferably programmed by radio transmission ofthe control characters and of the respective identification code fromthe programming unit of the remote communication station to the subjectworn unit. More preferably, the unit comprises switches as programminglockouts, particularly for preventing unintentional reprogramming.

In any RF link, errors are an unfortunate and unavoidable problem.Analog systems can often tolerate a certain level of error. Digitalsystems, however, while being inherently much more resistant to errors,also suffer a much greater impact when errors occur. Thus the presentinvention when used as a digital system, preferably includes an errorcontrol sub architecture. Preferably, the RF link of the presentinvention is digital. RF links can be one-way or two-way. One-way linksare used to just transmit data. Two-way links are used for both sendingand receiving data.

If the RF link is one-way error control, then this is preferablyaccomplished at two distinct levels, above and beyond the effort toestablish a reliable radio link to minimize errors from the beginning.At the first level, there is the redundancy in the transmitted data.This redundancy is performed by adding extra data that can be used atthe remote communication station or at some station to detect andcorrect any errors that occurred during transit across the airwaves.This mechanism known as Forward Error Correction (FEC) because theerrors are corrected actively as the signal continues forward throughthe chain, rather than by going back to the transmitter and asking forretransmission. FEC systems include but are not limited to Hamming Code,Reed-Solomon and Golay codes. Preferably, a Hamming Code scheme is used.While the Hamming Code scheme is sometimes maligned as being outdatedand underpowered, the implementation in certain embodiments of thepresent invention provides considerable robustness and extremely lowcomputation and power burden for the error correction mechanism. FECalone is sufficient to ensure that the vast majority of the data istransferred correctly across the radio link. Certain parts of the packetmust be received correctly for the receiver to even begin accepting thepacket, and the error correction mechanism in the remote communicationstation reports various signal quality parameters including the numberof bit errors which are being corrected, so suspicious data packets canbe readily identified and removed from the data stream.

Preferably, at a second, optional level, an additional line of defenseis provided by residual error detection through the use of a cyclicredundancy check (CRC). The algorithm for this error detection issimilar to that used for many years in disk drives, tape drives, andeven deep-space communications, and is implemented by highly optimizedfirmware within the electrode patch processing circuitry. Duringtransmission, the CRC is first applied to a data packet, and then theFEC data is added covering the data packet and CRC as well. Duringreception, the FEC data is first used to apply corrections to the dataand/or CRC as needed, and the CRC is checked against the message. If noerrors occurred, or the FEC mechanism was able to properly correct sucherrors as did occur, the CRC will check correctly against the messageand the data will be accepted. If the data contains residual errors(which can only occur if the FEC mechanism was overwhelmed by the numberof errors), the CRC will not match the packet and the data will berejected. Because the radio link in this implementation is strictlyone-way, rejected data is simply lost and there is no possibility ofretransmission.

More preferably, the RF link utilizes a two-way (bi-directional) datatransmission. By using a two-way data transmission the data safety issignificantly increased. By transmitting redundant information in thedata emitted by the electrodes, the remote communication station iscapable of recognizing errors and request a renewed transmission of thedata. In the presence of excessive transmission problems such as, forexample transmission over excessively great distances, or due toobstacles absorbing the signals, the remote communication station iscapable of controlling the data transmission, or to manipulate on itsown the data. With control of data transmission it is also possible tocontrol or re-set the parameters of the system, e.g., changing thetransmission channel. This would be applicable for example if the signaltransmitted is superimposed by other sources of interference then bychanging the channel the remote communication station could secure aflawless and interference free transmission. Another example would be ifthe signal transmitted is too weak, the remote communication station cantransmit a command to increase its transmitting power. Still anotherexample would be the remote communication station to change the dataformat for the transmission, e.g., in order to increase the redundantinformation in the data flow. Increased redundancy allows transmissionerrors to be detected and corrected more easily. In this way, safe datatransmissions are possible even with the poorest transmission qualities.This technique opens in a simple way the possibility of reducing thetransmission power requirements. This also reduces the energyrequirements, thereby providing longer battery life. Another advantageof a two-way, bi-directional digital data transmission lies in thepossibility of transmitting test codes in order to filter out externalinterferences such as, for example, refraction or scatter from thetransmission current. In this way, it is possible to reconstruct falselytransmitted data.

The remote communication station of various embodiments of the presentinvention can be any device known to receive RF transmissions used bythose skilled in the art to receive transmissions of data. The remotecommunication station by way of example but not limitation can include acommunications device for relaying the transmission, a communicationsdevice for re-processing the transmission, a communications device forre-processing the transmission then relaying it to another remotecommunication station, a computer with wireless capabilities, a PDA withwireless capabilities, a processor, a processor with displaycapabilities, and combinations of these devices. Optionally, the remotecommunication station can further transmit data both to another deviceand/or back. Further optionally, two different remote communicationstations can be used, one for receiving transmitted data and another forsending data. For example, with the wireless movement disordermonitoring system of the present invention, the remote communicationsystem of the present invention can be a wireless router, whichestablishes a broadband Internet connection and transmits thephysiological signal to a remote Internet site for analysis, preferablyby the subject's physician. Another example is where the remotecommunication system is a PDA, computer or cell phone, which receivesthe physiological data transmission, optionally re-processes theinformation, and re-transmits the information via cell towers, landphone lines or cable to a remote site for analysis. Another example iswhere the remote communication system is a computer or processor, whichreceives the data transmission and displays the data or records it onsome recording medium, which can be displayed or transferred foranalysis at a later time.

In many embodiments, information from the subject-worn device ispreferably uploaded or otherwise made available to clinicians,researchers, or other end users by means of wired or wirelesscommunication methods substantially instantly. Raw data, symptomquantification information, and any other data may be made immediatelyavailable to the end user for further analysis, review, or storage. Theinformation may be instantly uploaded to a remote communication station,may be packaged and delivered directly to a specific end user or groupof end users (for example by email), or, more preferably, may beinstantly uploaded to a secure cloud-based server for storage. When thedata is stored in a cloud-based server, the information is readily andimmediately available to be accessed by verified end users who areauthorized to gain access to the information while being securely storedand hidden from unauthorized users. This cloud-based system isparticularly useful for clinical trials and other such studies. Usingtraditional movement disorder symptom analysis systems, as discussedthroughout, subject data requires timely analysis and review, and thenseparate storing and collaboration of the information. For clinicaltrials, this timely process is multiplied by the number of subjects andthe number of tests/sessions each subject performs. The present systeminstead provides automated symptom quantification information, and thenimmediately makes that information available to the end user. There isno lengthy period of time required for clinician analysis and scoring ofthe raw data, no need for numerous iterations of tests due to clinicianand subject variability, and no need for manual entry of data. Instead,the present invention provides more accurate symptom quantificationinformation and immediately makes that data available to the end user.Thus, the present invention can substantially decrease the number ofsubjects required to accurately and sufficiently provide requiredinformation for clinical trials. Additionally, the information or datamay be immediately made available to a clinician who can diagnose ornotice side effects that just took place, as opposed to later in time,and can ensure immediate compliance with the testing protocols. Stillfurther, one clinician or end user may be able to more accurately andefficiently monitor numerous subjects without the need for intensive andunreliable subjective analysis of movement data. This last aspect hasthe added benefit of decreasing the amount and cost of travel for thesubjects and clinicians, thus reducing the cost of care and/or clinicalstudies even further. Preferably, information is made available inreal-time. By real-time, it is meant that preferably information isuploaded and made available in less than 30 minutes after completion ofa test and calculation of symptom quantification. More preferably,information is uploaded and made available in less than 20 minutes aftercompletion of a test and calculation of symptom quantification. Stillmore preferably, information is uploaded and made available in less than15 minutes after completion of a test and calculation of symptomquantification. Yet more preferably, information is uploaded and madeavailable in less than 10 minutes after completion of a test andcalculation of symptom quantification. Even more preferably, informationis uploaded and made available in less than 5 minutes after completionof a test and calculation of symptom quantification. Still yet morepreferably, information is uploaded and made available in less than 1minute after completion of a test and calculation of symptomquantification. Even yet more preferably, information is uploaded andmade available in less than 45 seconds after completion of a test andcalculation of symptom quantification. Yet still more preferably,information is uploaded and made available in less than 30 seconds aftercompletion of a test and calculation of symptom quantification. Evenstill more preferably, information is uploaded and made available inless than 15 seconds after completion of a test and calculation ofsymptom quantification. Yet even more preferably, information isuploaded and made available in less than 10 seconds after completion ofa test and calculation of symptom quantification. Still even morepreferably, information is uploaded and made available in less than 5seconds after completion of a test and calculation of symptomquantification. Still even yet more preferably, information is uploadedand made available in less than 1 second after completion of a test andcalculation of symptom quantification. Yet even still more preferably,information is uploaded and made available in less than 0.5 second aftercompletion of a test and calculation of symptom quantification. Mostpreferably, information is uploaded and made available substantiallysimultaneously with completion of a test and calculation of symptomquantification. Thus, the system may utilize a separate communicationstation to synchronize and communicate information with a remotecommunication station, but more preferably contains communicationcircuitry which can automatically, or semi-automatically send theinformation upon completion of a test. It is also important to note thatthe system preferably communicates data in a format which can be adaptedor integrated into existing data structure systems such that noproprietary program, algorithm, or data structure is required tocollect, analyze, and/or utilize the information. The data andinformation generated by the subject-worn device, and communicated to acloud-based server or directly to an end user is compatible with,readily adapted to or integrated with currently existing datastructures, or those later developed.

The digitized kinetic or physiological signal is then transmittedwirelessly to a remote communication station (FIG. 7). This remotecommunication station allows the subject wide movement. Preferably, theremote communication station can pick up and transmit signals fromdistances of greater than about 5 feet from the subject, more preferablygreater than about 10 feet from the subject, even more preferablygreater than about 20 feet from the subject, still even more preferablygreater than about 50 feet from the subject, still even more preferablygreater than about 200 feet from the subject, and most preferablygreater than about 500 feet from the subject. The remote communicationstation is used to re-transmit the signal based in part from thephysiological signal from the remote communication station wirelessly orvia the internet to another monitor, computer or processor system. Thisallows the physician or monitoring service to review the subjectsphysiological signals and if necessary to make a determination, whichcould include modifying the subject's treatment protocols.

Optionally, the system of the present invention includes some form ofinstruction, which can be in written form on paper or on a computermonitor, or on a video. Preferably, a video is used which instructs thesubjects to perform a series of tasks during which their kinetic motionand/or EMG can be measured. Since the system of the present invention ispreferably used in the subject's home, a video giving directions and/ordescribing various tasks to be performed by the subject is included withthe system. The video may be accessed or viewed for example but not byway of limitation through use of video tape, DVD, as part of computersoftware provided, through the internet, or the like. The directionscould include but are not limited to instructions on how to don thedevice, how to turn the device on, and the like. The description ofvarious tasks could include but is not limited to exercises which aretypically used by a technician, clinician or physician to evaluate asubject with a movement disorder including but not limited to handgrasps, finger tapping exercises, other movements and the like. Oneembodiment of a video includes the technician, clinician or physicianlooking into the camera, as they would a subject, and instructing themon device setup, instructing the subjects through each of the tasks tobe performed, providing verbal encouragement via video after a task, andasking subject's to repeat a task if it was not completed. Preferably,these video clips are edited and converted to a MPEG files using aPinnacle Studios digital video system that includes a fire-wire card andediting software. For movement disorders such as Parkinson's diseasepreferably the technician, clinician or physician instructs the userthrough multiple tasks as per the UPDRS guidelines including but notlimited to rest tremor, postural tremor, action tremor, all bradykinesiatasks (including but not limited to finger taps, hand grasps, andpronation/supination tasks), and/or rigidity tasks. More preferably, ifthe video is linked to the user interface software, the software willautomatically detect if a subject has performed the requested task andprovide feedback through the video to either repeat the task or continueto the next task.

Existing systems largely use interactive, observation-based methods inwhich clinicians or other trained individuals, as well as the subjectsthemselves, observe and report on the subject's symptoms and provide asubjective score relating to a quantification of the symptom severity.One such system that is widely accepted and known in the art is theUnified Parkinson's Disease Rating Scale (UPDRS) as mentioned above. TheUPDRS comprises several sections, each relating to a different groupingof tests which relate to a particular group of symptoms of Parkinson'sDisease. The several sections of the UPDRS include: Part I—evaluation ofmentation, behavior and mood; Part II—self-evaluation of the activitiesof daily life; Part III—evaluation of motor function (typicallyclinician-scored); Part IV—evaluation of complications of therapy; PartV—Hoehn and Yahr scale staging of the severity of Parkinson's Disease;and Part VI—Schwab and England Activities of Daily Living scale. Eachpart either requires the clinician to observe the subject's symptoms, orfor the subject to self-score the severity of symptoms and record his orperception of the symptoms for the clinician to later evaluate theinformation. Each part is comprised of a number of different tests oractivities, and each test or activity receives a score. This scorerelates to the perceived or observed severity of the symptom beingobserved during a particular test or activity. The individual test oractivity scores are then combined to provide an overall score for theparticular section of the test, and a total UPDRS score is also providedcombining the scores from each section. Each observation of a test oractivity introduces several degrees of variability and subjectivitybased on the evaluator's opinion of the information/data presented.

Many statistical metrics can be used to evaluate the reliability andrepeatability of a scale such as the UPDRS. Several of the most commonlyused and accepted metrics include standard error of measurement (SEM),minimal clinically important change or difference (MCIC/MCID), smallestdetectable difference (SDD), fluctuation, intraclass correlation (ICC),and minimal detectable change (MDC). These metrics each provide aquantitative analysis of how statistically accurate a rating or scoringscale or system is, and thus provide measures of the reliability andaccuracy of these scales and systems. The present invention aims toprovide an automated system which is more accurate and reliable thancurrently known scales and systems.

Using any of these metrics to measure sensitivity, repeatability, orreliability of a system typically requires the repetition of at leastone test, under circumstances that are as substantially similar aspossible. Therefore, although in clinical practice tests may be repeatedas infrequently as once a month (or sometimes longer), in order tomeasure the sensitivity, repeatability, or reliability of a system, itis often preferable to repeat the test(s) in a shorter period of time.For purposes of the present invention, this shorter time periodspecifically for measuring sensitivity, repeatability, or reliability ofa system is referred to as real-time measurement, (e.g., real-time ICC,real-time MDC, and the like), and corresponds to any of the above orother metrics that may be used to assess the system. Preferably, forreal-time system assessment, the test(s) are repeated within 4 hours.More preferably, for real-time system assessment, the test(s) arerepeated within 3 hours. Still more preferably, for real-time systemassessment, the test(s) are repeated within 2.5 hours. Yet morepreferably, for real-time system assessment, the test(s) are repeatedwithin 2 hours. Even more preferably, for real-time system assessment,the test(s) are repeated within 1.5 hours. Still yet more preferably,for real-time system assessment, the test(s) are repeated within 1 hour.Even yet more preferably, for real-time system assessment, the test(s)are repeated within 45 minutes. Yet still more preferably, for real-timesystem assessment, the test(s) are repeated within 30 minutes. Evenstill more preferably, for real-time system assessment, the test(s) arerepeated within 20 minutes. Yet even more preferably, for real-timesystem assessment, the test(s) are repeated within 15 minutes. Stilleven more preferably for real-time system assessment, the test(s) arerepeated within 10 minutes. Most preferably, for real-time systemassessment, the test(s) are repeated substantially immediately uponcompletion of the previous test. The only significant limitation on howquickly the test(s) may be repeated in order to assess the system'ssensitivity, repeatability, or reliability is the length of time itactually takes to perform a given test, and to repeat that test.

Standard error of measurement (SEM) estimates how repeated measurementsby an instrument or clinician tend to be distributed and thus how thescore varies from measurement to measurement. The formula forcalculating SEM is presented in Equation 1:SEM=SD×√{square root over (1−r)}.  1)SD is the standard deviation of measurements, and r is the reliabilitycoefficient, where the reliability coefficient represents thevariability of the scores of the test and indicates the range of thescores that can be expected upon retesting.

Minimal clinically important change or minimal clinically importantdifference (MCIC/MCID) is described as the smallest difference thatclinicians and/or subjects would care about or notice. This is a whollysubjective metric in that it is judged by the subject or by experts inthe field, typically based on inputs from subjects. This metric focuseson the subject's perceived result from a given therapy or treatment andwhether the result is significant enough to effect an actual discerniblechange in his or her function or life. The value for MCIC/MCID istypically determined based on the subject's input by way of questioningor observing the subject, or having the subject provide a report in somemanner.

Intraclass correlation (ICC) is a statistical measure of the reliabilityof the rating or score scale or system in that it measures the agreementbetween groups of values, typically the values of the scores or ratingsfor a group of tests where each test in the group is a repeat of thefirst, and is conducted under the same or substantially identicalcircumstances—hence ICC is a measure of test-retest reliability. ICC canbe used to assess test-retest reliability of a single observer (in thecase of the present invention a single clinician or device forcalculating symptom severity scores) or among several observersmeasuring the same quantity. The modern, and commonly accepted formulafor calculation of ICC is presented in Equation 2:

$\begin{matrix}{r = {{\frac{K}{K - 1} \times \frac{N^{- 1} \cdot {\sum\limits_{n = 1}^{N}( {{\overset{\sim}{x}}_{n} - \overset{\sim}{x}} )^{2}}}{s^{2}}} - {\frac{1}{K - 1}.}}} &  2 )\end{matrix}$K is the number of data values per group compared, s is the standarddeviation, and {tilde over (x)}_(n) is the sample mean of the n^(th)group. Values for ICC (r) are typically positive value between 0 and 1representing the ratio of total variance due to variation betweengroups. Thus, as the ICC value approaches 1, the system, test, metric,etc. is less variable and is more reliable and repeatable. For purposesof the present invention, the sample size for ICC measurements (i.e.,number of iterations of the same movement disorder test, movement,activity or motion) is preferably at a minimum two, though is preferablyhigher. More preferably, at least three iterations of the movementdisorder test are used to calculate the ICC for the given test. Stillmore preferably, at least four iterations of the movement disorder testare used to calculate the ICC for the given test. Yet more preferably,at least five iterations of the movement disorder test are used tocalculate the ICC for the given test. Even more preferably, at leastseven iterations of the movement disorder test are used to calculate theICC for the given test.

Related to test-retest reliability is the minimal detectable change(MDC), the minimum amount of change on a rating scale or instrument thatis not likely due to chance or variation in measurement. Score changesthat are less than the MDC value are considered to be indistinguishablefrom measurement error, but score changes greater than the MDC can beattributed to the subject improvement rather than measurement error.Thus, if a subject's score change is greater than the MDC value, thatsubject is considered to noticeably benefit from the particular therapyor treatment which accounted for the change in score. MDC calculation issimilar to that for SEM (see above), and formula for calculating MDC ispresented in Equation 3:MDC=z˜score_(conf level)×SD_(baseline)×√{square root over (2(1−r_(test-retest)))}  3)The z-score is representative of the confidence interval from a normaldistribution, SD is the standard deviation at baseline, and r is thetest-retest reliability coefficient (sometimes ICC). Many in the artchoose to use a confidence interval of 90%, while many others choose touse 95%. When a confidence interval of 95% is used, many of thoseskilled in the art define this increased precision MDC value as thesmallest detectable change (SDD). The MDC (or SDD) values may bepresented with varying units depending on the item, quantity, or valuebeing measured. For example, if an overall section of the UPDRS (e.g.,UPDRS-III, the motor section) is being scored and compared against otherscores for the same section, then the MDS would have no units attachedbecause the value being measured has no units—it is a raw scorecharacterized by a positive integer. However, where a single test,event, quantity, etc. is being evaluated, for example a functional reachtest (measured in centimeters) or ambulation tests (measured in distance(meters) or time (seconds)), the MDC value may have a unit attachedrepresentative of the units used to measure the results of theparticular test. This stands to reason due to the nature of the MDC (orSDD) measurement which quantifies the minimal amount of change in thoseunits that is detectable.

The above metrics may be used to measure a system's reliability andaccuracy, particularly with regards to repeatability of results, andthus determine how sensitive a system is to variability in theunderlying measurements. With respect to the present invention, it ispreferable that the devices or methods meet certain thresholds forsensitivity to variability, and thus these metrics can be used to defineacceptable levels of such sensitivity. In many embodiments, the presentinvention calculates a series of symptom quantification measures whichcan be calculated for any test or series of tests the subject performs.The symptom quantification metrics may be calculated for a single test(e.g., resting tremor, finger taps, hand movements, and the like), oracross a series of tests (e.g. UPDRS-III as a whole, which combines theabove individual tests with others). For the purpose of the presentinvention, a “test” is defines as any activity or action that thesubject performs in order to gauge and measure the movement disordersymptoms present while performing said activity or action. Therefore,these symptom quantification measures may be used to measure thesensitivity of the system using the above metrics, and preferably thesystem meets a minimum threshold for sensitivity with respect to eachmetric. With respect to ICC, the present invention preferably providessymptom quantification measures for repeated tests with an ICC of atleast about 0.50. More preferably, the present invention providessymptom quantification measures for repeated tests with an ICC of atleast about 0.55. Still more preferably, the present invention providessymptom quantification measures for repeated tests with an ICC of atleast about 0.60. Yet more preferably, the present invention providessymptom quantification measures for repeated tests with an ICC of atleast about 0.63. Even more preferably, the present invention providessymptom quantification measures for repeated tests with an ICC of atleast about 0.65. Still yet more preferably, the present inventionprovides symptom quantification measures for repeated tests with an ICCof at least about 0.67. Even still more preferably, the presentinvention provides symptom quantification measures for repeated testswith an ICC of at least about 0.70. Still even more preferably, thepresent invention provides symptom quantification measures for repeatedtests with an ICC of at least about 0.73. Yet still more preferably, thepresent invention provides symptom quantification measures for repeatedtests with an ICC of at least about 0.75. Even yet more preferably, thepresent invention provides symptom quantification measures for repeatedtests with an ICC of at least about 0.77

With respect to MDC, the thresholds may vary widely depending on whethera single test, or a group of tests, is being performed and measuredbecause the measurable units for each test may vary. Furthermore, theminimal detectable change value will be different for each individualtest or set of tests. Some tests may have a scale of 0 to 4 while othersmay measure ranges from 1-100. Therefore, it may be preferable tomeasure the MDC of a given test based on the percentage of the overallscale for that particular test. Regardless of the test being performed,the present invention preferably provides symptom quantificationmeasures for repeated tests with an MDC corresponding to about 35% orless of the total test score scale. More preferably, the presentinvention provides symptom quantification measures for repeated testswith an MDC corresponding to about 30% or less of the total test scorescale. Yet more preferably, the present invention provides symptomquantification measures for repeated tests with an MDC corresponding toabout 27% or less of the total test score scale. Still more preferably,the present invention provides symptom quantification measures forrepeated tests with an MDC corresponding to about 25% or less of thetotal test score scale. Even more preferably, the present inventionprovides symptom quantification measures for repeated tests with an MDCcorresponding to about 23% or less of the total test score scale. Stillyet more preferably, the present invention provides symptomquantification measures for repeated tests with an MDC corresponding toabout 20% or less of the total test score scale. Even yet morepreferably, the present invention provides symptom quantificationmeasures for repeated tests with an MDC corresponding to about 17% orless of the total test score scale.

The present invention includes various methods of measuring and scoringthe severity of a subject's movement disorder. These methods include anumber of steps which may include but are not limited to providing adevice to a subject, the device comprising at least one sensor having asignal corresponding to a subject's external body motion associated witha movement disorder; measuring a subject's external body motion;transmitting a signal based in part on the subject's measured externalbody motion; receiving the transmitted signal; calculating substantiallyin real time with the processor a symptom quantification measure basedat least in part on the signal from the at least one sensor; downloadingdata from memory; and scoring the severity of a subject's movementdisorder based in part on the transmitted or downloaded signal.Optionally, an electromyogram of the subject's muscle activity may beobtained and used in part to score the severity of the subject'smovement disorder.

The step of providing a device to a subject preferably refers to thevarious embodiments of a device as described herein. The device ispreferably one used for measuring and quantifying the severity of asubject's movement disorder symptoms. This step may include providinginstructions based on which the subject would be able to apply andremove the device so that it may be worn for testing and removed whennot testing. In several embodiments, the device preferably has at leastone sensor, though in many other embodiments the device preferably hasat least two sensors, and in still other embodiments at least threesensors. In all embodiments, the sensors of the provided device have asignal wherein that signal corresponds to a perceived, measured orsensed movement of the subject's body. Preferably, the sensorscorrespond to external motion of the subject's body such that theyperceive, measure or sense body movements that correspond to movementdisorder symptoms.

Many embodiments further comprise a step of measuring the subject'sexternal body motion with the device and the at least one, two, or threesensors of the device. For the purposes of the present invention, andspecifically with regard to measuring the sensitivity of the device, themeasurement of the subject's external body motion is preferably carriedout while the subject is performing at least one test, activity,movement, or motion. Also preferably, the at least one test, activity,movement, or motion corresponds to a particular movement disorder test.By way of non-limiting example, Section III of the UPDRS proscribesvarious tests for the subject to perform in order for the clinician toscore the severity of motor symptoms during those tasks, some of thetests include finger-tapping, heel tapping, standing up from a chair,and the like. Each of these tasks is considered a test and can be usedto measure a different aspect, characteristic or symptom of thesubject's potential movement disorder. Other scales and tests may beused for various movement disorders, or for different symptoms.Regardless of the test, activity, movement or motion performed, thedevice measures the subject's external body motion while it is beingperformed. Preferably, other surrounding factors and circumstances maybe recorded as well, such as the time of day the test is performed, thetime at which the last dose of medication was administered, and otherenvironmental factors that would allow the test to be repeated under themost identical conditions possible at a later time. As the device, andmore particularly the sensor(s) of the device measure the subject'sexternal body motion, the sensor(s) transform the measurement into asignal which corresponds to the measured external body motion.

Many embodiments of the present invention further comprise a step oftransmitting the signal from the sensor to a processor. The variousmethods and modalities by which the signal may be transmitted aredescribed throughout, but the signal may be transmitted throughhardwired communication, though is preferably transmitted wirelessly.The processor, as described in greater detail above, comprises varioushardware and programs or algorithms for pre-processing and processingthe signal(s) of the sensor(s). The signal(s) are transmitted from thesensor(s) to the processor so that the processor can carry out therequired quantification steps described below.

Many embodiments of the present invention further include the step ofquantifying the severity of the subject's movement disorder symptom. Inmany such embodiments, the quantification of a symptom is provided inthe form of a symptom quantification measure or score. The scale of thesymptom quantification measure or score depends on the particular typeof sensor used, and the particular test, activity, movement or motionthe subject is performing. Preferably calculation of the symptomquantification measure or score is performed by the processorsubstantially in real time. As disclosed herein, by real time, it ismeant that the quantification measure or score is preferably calculatedin less than about 30 minutes of the subject performing the test and thesubject's external body motion being measured. More preferably, thequantification measure or score is preferably calculated in less thanabout 1 minute of the subject performing the test and the subject'sexternal body motion being measured. Still more preferably, thequantification measure or score is preferably calculated in less thanabout 30 seconds of the subject performing the test and the subject'sexternal body motion being measured. Yet more preferably, thequantification measure or score is preferably calculated in less thanabout 15 seconds of the subject performing the test and the subject'sexternal body motion being measured. Even more preferably, thequantification measure or score is preferably calculated in less thanabout 10 seconds of the subject performing the test and the subject'sexternal body motion being measured. Yet still more preferably, thequantification measure or score is preferably calculated in less thanabout 5 seconds of the subject performing the test and the subject'sexternal body motion being measured. Even still more preferably, thequantification measure or score is preferably calculated in less thanabout 1 second of the subject performing the test and the subject'sexternal body motion being measured. Still yet more preferably, thequantification measure or score is preferably calculated in less thanabout 0.1 seconds of the subject performing the test and the subject'sexternal body motion being measured. Even yet more preferably, thequantification measure or score is preferably calculated in less thanabout 0.01 seconds of the subject performing the test and the subject'sexternal body motion being measured. In all such embodiments, theprocessor calculates the symptom quantification measure or score basedat least in part on the signal(s) received from the sensor(s) where saidsignal(s) correspond to the measured external body motion of thesubject.

Many embodiments of the present invention, particularly those pertainingto the sensitivity and accuracy of the device and/or measurements, mayrequire a further step(s) wherein at least one of the above steps arerepeated as described. Some embodiments may utilize a single additionalrepetition of at least one of the above steps, though other embodimentsmay use multiple iterations. Most notably, the steps of measuring thesubject's external body motion with the device comprising a sensor(s)while the subject performs a movement disorder test, activity, movementor motion, transmitting a signal from the sensor(s) to the processor,and calculating with the processor a symptom quantification measure orscore are the steps most likely to be repeated at least once for thepurposes of checking or determining the sensitivity of the device and/ormethods. In such embodiments, the subject's external body motion ismeasured during the first movement disorder test, and the sensor(s)transmit a first signal to the processor which calculates a firstsymptom quantification measure or score based at least in part on thesignal(s) received during or after the first test. Subsequently, thesteps are repeated where the subject's external body motion is measuredduring a second movement disorder test, and the sensor(s) transmit asecond signal to the processor which calculates a second symptomquantification measure or score based at least in part on the signal(s)received during or after the second test. It is possible to carry outthis process in further iterations as well. When repeating a movementdisorder test for the purpose of checking or determining the system'ssensitivity, the second test is preferably performed under substantiallyidentical circumstances as the first movement disorder test. Forexample, the subject should perform the exact same test or tests thesecond time that were performed the first time. Additionally, the secondtest is preferably performed as near to the same time of day as thefirst test, and at the same point in the subject's medication cycle (ifthe subject is on medication) as possible. That is, if the subjecttypically takes movement disorder-related medication upon awaking in themorning, and did so on the day of the first test, that habit or processshould be repeated on the day of the second test. In other words, thecircumstances surrounding the first and second tests should be as nearto identical as possible in order to eliminate extra variables that mayaffect the results of the test in the form of symptom severity. The sameholds true for any subsequent iterations of the testing procedure aswell. The end result is that the two tests provide a basis on which thesensitivity of the system may be measured in order to determine howaccurate, consistent, and repeatable measurement results are with thegiven device and methods. As discussed herein, sensitivity may bemeasured by various metrics including intraclass correlation (ICC),minimum detectable change (MDC), smallest detectable difference(SDD—often interchangeable with and MDC measurement with a 95%confidence interval), and the like.

S FIGS. 8-10 show flow diagrams for various operating modes of thesystem of the present invention. These operating modes should be viewedas examples but not limitations to the present invention and understoodthat these are but a few of the methods of using the system of thepresent invention. FIG. 8 is a flow diagram for a continuous operatingmode or method for the system of the present invention. In thisembodiment, the subjects continually wear at least one external sensormodule 80. The external sensor module, which can measure kinetic motionand/or EMG is continually measured by the external sensor module 82.Data from the external sensor module is continuously sampled and storedto memory within a subject worn transceiver module 84. During batteryrecharging of the device when the subject is not wearing the subjectcomponents, the subject components are connected through a hardwire USBlink to the subject PC. The stored data is then either transmitted viaan RF link to a transceiver unit connected to a computer 86 ortransferred through the USB port to the computer. Software algorithms inthe computer process kinetic and/or EMG data to quantify the severity ofthe movement disorder symptom occurring 87. The processed information isthen used to generate subject reports or data 88, and the reports ordata are transmitted to technician, clinician or physician for review89.

FIG. 9 is a flow diagram for a task operating mode or method for thesystem of the present invention. In this mode the subjectsintermittently wear at least one external sensor module at technician,clinician or physician prescribed times 100. The subjects may start thesubject computer user interface program, preferably with the touch of asingle button. The computer transceiver “wakes up” the subject worntransceiver module 102 or the clinical video on the subject computerinstructs the subject to press a button on the transceiver module tomanually “wake up” the unit. The subject performs a series of tasks asdirected by a clinical video, which preferably is viewed on thesubject's computer monitor 103. The data from the external sensor moduleis then sampled and transmitted by radio frequency with the subject worntransceiver module during the tasks 104. The data is received by atransceiver unit connected to the computer 105. The data transmissionlasts approximately or only as long as the same time as a programmedcollection interval, the subject worn transceiver unit then enters intoa “sleep state” 106. Software algorithms in a computer connected to thecomputer transceiver unit process the kinetic motion and/or EMG data toquantify severity of the movement disorder symptom occurring 107. Theprocessed information is then used to generate subject reports or data108, and the reports or data are transmitted to technician, clinician orphysician for review 109.

FIG. 10 is a flow diagram for a combination operating mode or method forthe system of the present invention. In this mode, the subjectcontinually wears at least one external sensor module 110. The externalsensor module, which can measure kinetic motion and/or EMG iscontinually measured by the external sensor module 111. Data from theexternal sensor module is continuously sampled and stored to memory onthe subject worn transceiver module 114. This data is then downloaded tothe subject computer at a later time. Software algorithms in thecomputer process kinetic and/or EMG data to quantify the severity of themovement disorder symptom occurring 116. The processed information isthen used to generate subject reports or data 117, and the reports ordata are transmitted to technician, clinician or physician for review118. This method, however, varies from the method described in FIG. 8 inthat at technician, clinician, physician or computer at randomlyspecified times alerts the subject start or has computer starts a video112, and alerts the subject to perform a series of tasks as directed bythe clinical video, which is preferably on the subject's computermonitor 113. During these tasks, data is transmitted by the user wornreceiver module and is received by a transceiver unit connected to acomputer 115. Software algorithms in the computer process kinetic and/orEMG data to quantify the severity of the movement disorder symptomoccurring 116. The processed information is then used to generatesubject reports or data 117, and the reports or data are transmitted totechnician, clinician or physician for review 118.

The portable movement disorder device of the present invention formeasuring the severity of a subject's movement disorder can be worn inany way likely to provide good data on a subject's movement disorder.Examples would include but are not limited to the use of the device onthe subject's hand and/or arm; legs, and/or head. Preferably, themovement disorder device is on the arm and/or hand of the subject. FIGS.6 and 7 and show a schematic of a movement disorder device on asubject's lower arm and hand. In this embodiment, the subject's kineticmotion is measured by a kinetic sensor board (also known as externalsensor module) 50. The external sensor module 50 is held firmly to thesubject's finger 51 by a hood and loop strap 52. The external sensormodule 50 is connected to a subject worn transceiver module 64 viaelectrical pathways or wires 54. Optionally, the device may also have atleast one EMG electrodes (not shown).

Preferably, the subject worn transceiver module in this embodiment isreasonably small size. Achieving the wrist mount design of thisembodiment require the size of the radio used for the device be greatlyreduced. Preferably, a commercially available chip (blue toothtechnology) is used that can transmit up to 200 ft. Not only will thisgreatly reduce the size of the device, but the transceiver capabilitywill allow two-way communications between the subject worn unit and thecomputer unit.

The two-way capability in this particular embodiment will providemultiple benefits. First, by having two-way communications, the unitwill be capable of utilizing a protocol where data packets can be resentif corrupted during transmission. Another benefit is that severalsubject worn units could potentially communicate with a single basestation clinician PC. In this scenario, the subject units occupydedicated time slots to transmit their information. Several subject wornunits could operate with a single computer base station in a hospital orhome setting. Additionally, multiple units may be worn on a subject tomonitor tremor in both hands at the same time. A final benefit of thetwo-way protocol is that configuration information can be sent to thesubject unit over the radio link including power level, frequency, andshut down modes. Shut down modes could be of great benefit for this typeof system where the clinical PC can command the subject units to powerdown between tests thus conserving battery life in the subject unit.Essentially, the technician, clinician, or physician will be able toprogram the system for continuous recording or to record at certaintimes for specified intervals.

Preferably, the radio design of this specific embodiment is implementedusing a highly integrated radio chip (Bluetooth® technology) whichrequires very few external components, consumes less power than adiscrete radio design, and requires less physical area than a discretedesign. More preferably, the radio chip takes incoming clock and dataand produces a Frequency Modulated carrier when configured as atransmitter, and performs the opposite function when configured as areceiver. This high level of integration makes the only componentrequired to interface to the radio section a unit microcontroller.

With few components and high level of integration, the radio sectionshould be easy to manufacture, have low component cost, and have highfield reliability. Preferably, the IC or microprocessor has acontrollable RF power output levels and by using the two-way protocoldescribed above, the radio link can operate at a level high enough toensure reliable data transfer while conserving unit power. Finally, themost preferably, the IC or microprocessor can operate anywhere from 300MHz to 2.4 GHz providing great flexibility when the system is developedto ensure optimum operation. The 2.4 GHz band is the preferableoperating band.

FIG. 11 is a flow diagram for one embodiment of the software used in thepresent invention. Analog outputs 151, 152 from the accelerometer andgyroscope are converted to linear acceleration and angular velocity witha scaling factor. The linear accelerations and angular velocity inputsare then bandpass filtered 153 to prevent biasing and remove DC drift.The linear acceleration is double integrated to yield linear position.The derivative 154 of the angular velocity is calculated to determineangle. The three dimensional translation and rotation 155 of the moduleis computed from the information from the three orthogonalaccelerometers and three orthogonal gyroscopes. The root mean square(RMS) value of the continuous time EMG signal is calculated overdiscrete time windows. The amplitude and frequency 156 of the processedEMG signal is calculated. Specific variables are then computed for eachParkinson's symptom based on the processed kinetic and EMG data. Tremorsymptom variables may include but are not limited to the peak frequencyof the kinetic sensors, the average amplitude of the kinetic sensors,the average power of the kinetic sensors, and the frequency of the EMGsignals. Bradykinesia symptom variables may include but are not limitedto the peak frequency of EMG or kinetic data, the average amplitude ofthe kinetic sensors, the average power of the EMG or kinetic sensors,the number of hesitations that occur in a subjects movement, or thelinear or exponential fit coefficients used to fit a model to theamplitude of a subject's movement over time. Rigidity symptom variablesmay include but are not limited to range of motion and EMG amplitude.Dyskinesia symptom variables may include but are not limited to theoutput of a neural network trained to recognize dyskinesia from othermovements using the kinetic sensor data as inputs. The value of eachsymptom variable for a particular symptom is used in an algorithm thatmay include but are not limited to multiple linear regression models orneural networks to fit the symptom variables to the qualitativeclinicians Unified Parkinson's Disease Rating Scale scores for thatsymptom 157.

The present invention further includes a drug delivery system. The drugdelivery system utilizes in part the input from the external sensors orthe scoring of the severity of the subject's movement disorder or themovement disorder symptoms as input into a closed loop control system todeliver medication to lessen or relieve the symptoms of the disorder, orto appropriately treat the disorder in a non-symptomatic way. The drugdelivery system comprises the at least one external sensor having asignal for measuring a subject's external body motion or a physiologicalsignal associated with a movement disorder. The drug delivery systemcomprises at least one external sensor being described earlier in theapplication. The drug delivery system further comprises a reservoir forsome form of medication, preferably liquid, that can either be deliveredto the subject internally or transcutaneously. The system furthercomprises an actuator which when activated and deactivated allows themedication to be delivered from the reservoir to the subject. Finally,the system further comprises a closed-loop control system whichactivates and deactivates the actuator based in part on a signal fromthe at least one external sensor.

FIG. 12 is a flow diagram for one embodiment of a closed-loop drugdelivery system of the present invention. In this embodiment, thesubjects continually wear at least one external sensor module 121.Kinetic motion and/or EMG is continually measured by the external sensormodule 122. Data from the external sensor module is continuously sampledand transmitted by radio frequency with a subject worn transceivermodule 123. The transmitted data is received by a transceiver unitconnected to a reservoir system 124 with embedded processing. Softwarealgorithms process kinetic and/or EMG data to quantify the severity ofthe movement disorder symptom occurring 124. The software algorithmstrigger the release of medication based on the subject's symptoms 126,or the overall severity of the movement disorder 125. The processedinformation is then used to generate subject reports or data 127, andthe reports or data are transmitted to technician, clinician orphysician for review 128.

FIG. 13 is a schematic diagram showing placement of various componentsof closed loop drug delivery system with an implantable reservoir. InFIG. 13, the subject 55 is wearing a closed loop drug delivery system.The closed loop drug may have an external sensor module 50, a subjectworn transceiver module 64, EMG electrodes 60, a reservoir 170 forholding medication with an embedded transceiver and processor andactuator for allowing delivery (not shown), and a controller foractivating and deactivating the actuator based in part on the signalfrom the at least one of the sensor modules 50. In this example areservoir 170 being implanted into the abdomen 9 of the subject. Thereservoir 170 containing medication, which is released into thesubject's body through activation of an actuator. The respectivetransceiver module 64 being connected to the EMG electrodes 60 andexternal sensor modules 50 via electrical pathways or wires (not shown).The transceiver module 64 being further being connected eitherwirelessly or via electrical pathways or wires (not shown) to acontroller (not shown), which activates and deactivates an actuator (notshown) to release medication from the implantable reservoir 170.

FIG. 14 is a schematic diagram showing placement of various componentsof a closed loop drug delivery system with an external reservoir totranscutaneous delivery. In FIG. 14, the subject 55 is wearing a closedloop drug delivery system. The closed loop drug delivery system may havean external sensor module 50, a subject worn transceiver module 64, EMGelectrodes 60, a reservoir 180 for holding medication with an embeddedtransceiver and processor and actuator for allowing delivery (notshown), and a controller for activating and deactivating the actuatorbased in part on the signal from the at least one of the sensor modules50. In this example a reservoir 180 is attached externally to theabdomen 9 of the subject. The reservoir 180 containing medication, whichis released into the subject's body through activation of an actuator.The respective transceiver module 64 being connected to the EMGelectrodes 60 and external sensor module 50 via electrical pathways orwires (not shown). The transceiver module 64 being further beingconnected either wirelessly or via electrical pathways or wires (notshown) to a controller (not shown), which activates and deactivates anactuator (not shown) to release medication from the implantablereservoir 180.

FIG. 15 is a flow chart depicting the methods of several embodiments ofthe present invention for quantifying a subject's movement disordersymptoms where sensitivity is measured using intraclass correlation(ICC). First, a device comprising at least one sensor having a signalcorresponding to a subject's external body motion associated with amovement disorder is provided 200 to the subject. The at least onesensor may be of any variety described herein, including, but notlimited to accelerometers, gyroscopes, pressure sensors, force sensors,and the like. The step of providing 200 the device to the subject mayfurther comprise steps of giving instructions for the subject toproperly don or apply the device. Once the device has been provided 200to the subject, the next step is to measure the subject's external bodymotion 205 while the subject performs at least one first movementdisorder test, activity, movement or motion. The test, activity,movement or motion preferably corresponds to at least one symptom of amovement disorder in such a way that the test, activity, movement ormotion is likely to exhibit at least one symptom of a movement disorder.When the subject performs the test, activity, movement or motion the atleast one sensor of the device measures the external body motion of thesubject, including any movement disorder symptom motions that arepresent. Either after the test is complete, or during testing, a signalfrom the at least one sensor is transmitted to a processor 210. Theprocessor then calculates a symptom quantification measure or score 215from the first at least one test performed. This first symptomquantification measure or score is based at least in part on the signalreceived from the at least one sensor of the device corresponding to thesubject's external body motion during the first test, activity, movementor motion, and is preferably stored for later comparison, analysis,evaluation, recollection, or other uses. The symptom quantificationmeasure or score is preferably calculated 215 substantially in real timecorresponding to the performance and/or completion of the first movementdisorder test.

Subsequently, a second movement disorder test is performed. Similar toduring the first test, the device measures the subject's external bodymotion while the subject is performing the second test 220. This secondtest may be performed either immediately following the first test, or,more preferably, at a later time (e.g., up to 30 days later), but isperformed under substantially similar circumstances as the first test.Similarly, the second test is preferably the same test, activity,movement or motion (or set thereof) as the first movement disorder test.Again, the second signal from the at least one sensor is transmitted toa processor 225 for comparison, analysis, evaluation, recollection, orthe like. The processor similarly uses this second signal to calculate asecond symptom quantification measure or score 230. This process may berepeated any number of times, each time conducting the same movementdisorder test(s) comprising the same tests, activities, movements ormotions under substantially similar circumstances. The separate symptomquantification measures or scores can then be compared in order tocalculate various sensitivity metrics corresponding to therepeatability, accuracy, consistency and the like of the device, methodand/or system. In many embodiments, the separate symptom quantificationmeasures or scores are used to measure sensitivity by calculating theintraclass correlation (ICC) 235 of the symptom quantification measures,and preferably the ICC is at least about 0.60.

FIG. 16 is a flow chart depicting the methods of several embodiments ofthe present invention for quantifying a subject's movement disordersymptoms where sensitivity is measured using minimum detectable change(MDC). First, a device comprising at least one sensor having a signalcorresponding to a subject's external body motion associated with amovement disorder is provided 200 to the subject. The at least onesensor may be of any variety described herein, including, but notlimited to accelerometers, gyroscopes, pressure sensors, force sensors,and the like. The step of providing 200 the device to the subject mayfurther comprise steps of giving instructions for the subject toproperly don or apply the device. Once the device has been provided 200to the subject, the next step is to measure the subject's external bodymotion 205 while the subject performs at least one first movementdisorder test, activity, movement or motion. The test, activity,movement or motion preferably corresponds to at least one symptom of amovement disorder in such a way that the test, activity, movement ormotion is likely to exhibit at least one symptom of a movement disorder.When the subject performs the test, activity, movement or motion the atleast one sensor of the device measures the external body motion of thesubject, including any movement disorder symptom motions that arepresent. Either after the test is complete, or during testing, a signalfrom the at least one sensor is transmitted to a processor 210. Theprocessor then calculates a symptom quantification measure or score 215from the first test performed. This first symptom quantification measureor score is based at least in part on the signal received from the atleast one sensor of the device corresponding to the subject's externalbody motion during the first test, activity, movement or motion, and ispreferably stored for later comparison, analysis, evaluation,recollection, or other uses. The symptom quantification measure or scoreis preferably calculated 215 substantially in real time corresponding tothe performance and/or completion of the first movement disorder test.

Subsequently, a second movement disorder test is performed. Similar tothe first test, the device measures the subject's external body motionwhile the subject is performing the second test 220. This second testmay be performed either immediately following the first test, or, morepreferably, at a later time (e.g., up to 30 days later), but isperformed under substantially similar circumstances as the first test,and with the subject in a substantially similar disease state (e.g., asecond or subsequent test would not be conducted if the subject hadbroken his or her leg since the first test because the circumstances anddisease state would not be substantially similar). Similarly, the atleast one second test is preferably the same test, activity, movement ormotion (or set thereof) as the first movement disorder test. Again, thesecond signal from the at least one sensor is transmitted to a processor225 for comparison, analysis, evaluation, recollection, or the like. Theprocessor similarly uses this second signal to calculate a secondsymptom quantification measure or score 230. This process may berepeated any number of times, each time conducting the same movementdisorder tests comprising the same tests, activities, movements ormotions under substantially similar circumstances. The separate symptomquantification measures or scores can then be compared in order tocalculate various sensitivity metrics corresponding to therepeatability, accuracy, consistency and the like of the device, methodand/or system. In many embodiments, the separate symptom quantificationmeasures or scores are used to measure sensitivity by calculating theminimum detectable change (MDC) 240 of the symptom quantificationmeasures, and preferably the MDC represents at a change of about 25% orless of the total scale of the particular test(s). As noted herein, thescale and measurement units of each individual test will vary (e.g., agait test or test for standing up from a seated position may be measuredin time with a total maximum allowable time to set the scale, whereasother tests may be measured in unitless scores or different units suchas frequency, each with a different scale for maximum allowablemeasurements).

Various embodiments of the present invention may include a step wherebythe subject fills out a diary or log. Preferably, the diary or logspecifically relates to the subject's disease state at the time it isfilled out. Entries into the diary or log may be performed on a periodicbasis determined by a clinician or study administrator. When the subjectmakes an entry into the diary or log, such entry may be a personalaccount of the subject's condition and disease state, though morepreferably is a simplified input system whereby the subject merely thepresence of one disease state, such as by checking a box or clicking abutton. Exemplary disease states typically used in movement disorderstudies include “ON,” “OFF,” “ON with dyskinesias,” and “On withnon-troublesome dyskinesias,” or variants thereof. The disease state“ON” relates to time when the subject has taken medication, and thatmedication is providing a perceived benefit in improving the subject'smobility, such as by reducing stiffness and/or improving speed ofmovement. The disease state “OFF” relates to time when medication hasworn off and is no longer providing a benefit to the subject with regardto mobility and movement. The disease state “ON with dyskinesias”relates to time when the subject has taken medication that is still ineffect (i.e., has not worn off), but is still experiencing dyskinesiasthat interrupt the subject's mobility, function or movement, such asinvoluntary twisting or turning movements. Typically, in this diseasestate, the dyskinesias are perceived to be a side effect of themedication. The disease state of “ON with non-troublesome dyskinesias”relates to time when the subject has taken medication that is still ineffect (I.e., has not worn off), but is still experiencing dyskinesias;however, the dyskinesias are not causing any meaningful discomfort tothe subject and do not interfere with mobility, function or movement. Anexample of a condition that would qualify as “ON with non-troublesomedyskinesias” is a mild tremor. In other, more preferred embodiments, thedevice and system are able to automatically detect the presence of oneof these disease states without requiring the subject to manually fillout a diary or log. These embodiments with automated disease statedetection preferably include the disease state with other data that isrecorded and stored and/or transmitted.

FIG. 17 is a flow chart depicting the methods of several embodiments ofthe present invention for quantifying a subject's movement disordersymptoms where sensitivity is measured using intraclass correlation(ICC). First, a device comprising at least three sensors, each having asignal corresponding to a subject's external body motion associated witha movement disorder, is provided 203 to the subject. These at leastthree sensors may be of any variety described herein, including, but notlimited to accelerometers, gyroscopes, pressure sensors, force sensors,and the like. Preferably, at least one sensor is an accelerometer, andat least one sensor is a gyroscope. The step of providing 203 the devicecomprising at least three sensors to the subject may further comprisesteps of giving instructions for the subject to properly don or applythe device. Once the device has been provided 203 to the subject, thenext step is to measure the subject's external body motion 205 while thesubject performs at least one first movement disorder test, activity,movement or motion. The test, activity, movement or motion preferablycorresponds to at least one symptom of a movement disorder in such a waythat the test, activity, movement or motion is likely to exhibit atleast one symptom of a movement disorder. When the subject performs thetest, activity, movement or motion the at least three sensors of thedevice measure the external body motion of the subject, including anymovement disorder symptom motions that are present. Either after thetest is complete, or during testing, a first signal is transmitted to aprocessor 213. The first signal may actually comprise at least threeseparate signals, one corresponding to each of the at least threesensors of the device. Alternatively, this first transmitted signal maybe a composite signal representing a combination of signals from the atleast three sensors of the device. In either format, the transmissionfrom the device to the processor, whether a single composite signal orseveral individual sensor signals, constitutes a single signalrepresenting the measured external body motions during the at least onefirst movement disorder test. The processor then calculates a symptomquantification measure or score 215 from the at least one first testperformed. This first symptom quantification measure or score is basedat least in part on the signal(s) received from the at least threesensors of the device corresponding to the subject's external bodymotion during the first test, activity, movement or motion, and ispreferably stored for later comparison, analysis, evaluation,recollection, or other uses. The symptom quantification measure or scoreis preferably calculated 215 substantially in real time corresponding tothe performance and/or completion of the first movement disorder test.

Subsequently, a second movement disorder test is performed. Similar tothe first test, the device measures the subject's external body motionwhile the subject is performing the second test 220. This second testmay be performed either immediately following the first test, or, morepreferably, at a later time (e.g., up to 30 days later), but isperformed under substantially similar circumstances as the first test.Similarly, the second test is preferably the same test, activity,movement or motion (or set thereof) as the first movement disorder test.Again, the second signal from the at least three sensors are transmittedto a processor 227 for comparison, analysis, evaluation, recollection,or the like. Much like the first transmission, the second signal maycomprise a single composite signal or individual sensor signals. Theprocessor similarly uses this second signal to calculate a secondsymptom quantification measure or score 230. This process may berepeated any number of times, each time conducting the same movementdisorder tests comprising the same tests, activities, movements ormotions under substantially similar circumstances. The separate symptomquantification measures or scores can then be compared in order tocalculate various sensitivity metrics corresponding to therepeatability, accuracy, consistency and the like of the device, methodand/or system. In many embodiments, the separate symptom quantificationmeasures or scores are used to measure sensitivity by calculating theintraclass correlation (ICC) 235 of the symptom quantification measures,and preferably the ICC is at least about 0.60.

FIG. 18 is a flow chart depicting the methods of several embodiments ofthe present invention for quantifying a subject's movement disordersymptoms where sensitivity is measured using minimum detectable change(MDC). First, a device comprising at least three sensors, each having asignal corresponding to a subject's external body motion associated witha movement disorder, is provided 203 to the subject. These at leastthree sensors may be of any variety described herein, including, but notlimited to accelerometers, gyroscopes, pressure sensors, force sensors,and the like. Preferably, at least one sensor is an accelerometer, andat least one sensor is a gyroscope. The step of providing 203 the devicecomprising at least three sensors to the subject may further comprisesteps of giving instructions for the subject to properly don or applythe device. Once the device has been provided 203 to the subject, thenext step is to measure the subject's external body motion 205 while thesubject performs at least one first movement disorder test, activity,movement or motion. The test, activity, movement or motion preferablycorresponds to at least one symptom of a movement disorder in such a waythat the test, activity, movement or motion is likely to exhibit atleast one symptom of a movement disorder. When the subject performs thetest, activity, movement or motion the at least three sensors of thedevice measure the external body motion of the subject, including anymovement disorder symptom motions that are present. Either after thetest is complete, or during testing, a first signal is transmitted to aprocessor 213. The first signal may actually comprise at least threeseparate signals, one corresponding to each of the at least threesensors of the device. Alternatively, this first transmitted signal maybe a composite signal representing a combination of signals from the atleast three sensors of the device. In either format, the transmissionfrom the device to the processor, whether a single composite signal orseveral individual sensor signals, constitutes a single signalrepresenting the measured external body motions during the at least onefirst movement disorder test. The processor then calculates a symptomquantification measure or score 215 from the at least one first testperformed. This first symptom quantification measure or score is basedat least in part on the signal(s) received from the at least threesensors of the device corresponding to the subject's external bodymotion during the first test, activity, movement or motion, and ispreferably stored for later comparison, analysis, evaluation,recollection, or other uses. The symptom quantification measure or scoreis preferably calculated 215 substantially in real time corresponding tothe performance and/or completion of the first movement disorder test.

Subsequently, a second movement disorder test is performed. Similar tothe first test, the device measures the subject's external body motionwhile the subject is performing the second test 220. This second testmay be performed either immediately following the first test, or, morepreferably, at a later time (e.g., up to 30 days later), but isperformed under substantially similar circumstances as the first test.Similarly, the second test is preferably the same test, activity,movement or motion (or set thereof) as the first movement disorder test.Again, the second signal from the at least three sensors are transmittedto a processor 227 for comparison, analysis, evaluation, recollection,or the like. Much like the first transmission, the second signal maycomprise a single composite signal or individual sensor signals. Theprocessor similarly uses this second signal to calculate a secondsymptom quantification measure or score 230. This process may berepeated any number of times, each time conducting the same movementdisorder tests comprising the same tests, activities, movements ormotions under substantially similar circumstances. The separate symptomquantification measures or scores can then be compared in order tocalculate various sensitivity metrics corresponding to therepeatability, accuracy, consistency and the like of the device, methodand/or system. In many embodiments, the separate symptom quantificationmeasures or scores are used to measure sensitivity by calculating theminimum detectable change (MDC) 240 of the symptom quantificationmeasures, and preferably the MDC represents at a change of about 25% orless of the total scale of the particular test(s). As noted herein, thescale and measurement units of each individual test will vary (e.g., agait test or test for standing up from a seated position may be measuredin time with a total maximum allowable time to set the scale, whereasother tests may be measured in unitless scores or different units suchas frequency, each with a different scale for maximum allowablemeasurements).

FIG. 19 is a flow chart depicting the methods of several embodiments ofthe present invention for quantifying a subject's movement disordersymptoms where sensitivity is measured using intraclass correlation(ICC). First, a device comprising at least one sensor, the at least onesensor having a signal corresponding to a subject's external body motionassociated with a movement disorder, is provided 200 to the subject. Theat least one sensor may be of any variety described herein, including,but not limited to accelerometers, gyroscopes, pressure sensors, forcesensors, and the like. The step of providing 200 the device comprisingat least three sensors to the subject may further comprise steps ofgiving instructions for the subject to properly don or apply the device.Once the device has been provided 200 to the subject, the next step isto measure the subject's external body motion 245 while the subjectperforms at least two first movement disorder tests, activity, movementor motion. Preferably, each of the at least two first tests belong orcorrespond to the same symptom group of classification. For example, ifthe tests are performed under the guidelines of the UPDRS, the each ofthe at least two test would correspond to the same grouping or sectionof the UPDRS, such as the Motor Examination section (UPDRS-III), or thelike. Different testing methods or protocols may have differentgroupings or classifications of symptoms, and preferably each of the atleast two tests performed correspond to the same grouping orclassification in whichever method or protocol is used. The at least twotests, activities, movements or motions preferably correspond to atleast one symptom of a movement disorder in such a way that the test,activity, movement or motion is likely to exhibit at least one symptomof a movement disorder. When the subject performs the at least twotests, activities, movements or motions the at least one sensor of thedevice measures 245 the external body motion of the subject, includingany movement disorder symptom motions that are present. Either after thetest is complete, or during testing, a signal from the at least onesensor is transmitted to a processor 250. The processor then calculatesa symptom quantification measure or score 255 from the at least twofirst tests performed. This first symptom quantification measure orscore is based at least in part on the signal received from the at leastone sensor of the device corresponding to the subject's external bodymotion during the at least two first tests, activities, movements ormotions, and is preferably stored for later comparison, analysis,evaluation, recollection, or other uses. The symptom quantificationmeasure or score is preferably calculated 255 substantially in real timecorresponding to the performance and/or completion of the first movementdisorder test.

Subsequently, at least two second movement disorder tests are performed.Similar to the at least two first tests, the device measures thesubject's external body motion while the subject is performing the atleast two second tests 260. The at least two second tests may beperformed either immediately following the first tests, or, morepreferably, at a later time (e.g., up to 30 days later), but areperformed under substantially similar circumstances as the first tests.Similarly, the second tests are preferably the same tests, activities,movements or motions as the first movement disorder tests. Again, thesecond signal from the at least one sensor is transmitted to a processor265 for comparison, analysis, evaluation, recollection, or the like. Theprocessor similarly uses this second signal to calculate a secondsymptom quantification measure or score 270. This process may berepeated any number of times, each time conducting the same movementdisorder tests comprising the same tests, activities, movements ormotions under substantially similar circumstances. The separate symptomquantification measures or scores can then be compared in order tocalculate various sensitivity metrics corresponding to therepeatability, accuracy, consistency and the like of the device, methodand/or system. In many embodiments, the separate symptom quantificationmeasures or scores are used to measure sensitivity by calculating theintraclass correlation (ICC) 275 of the symptom quantification measures,and preferably the ICC is at least about 0.60.

FIG. 20 is a flow chart depicting the methods of several embodiments ofthe present invention for quantifying a subject's movement disordersymptoms where sensitivity is measured using intraclass correlation(ICC). First, a device comprising at least one sensor, the at least onesensor having a signal corresponding to a subject's external body motionassociated with a movement disorder, is provided 200 to the subject. Theat least one sensor may be of any variety described herein, including,but not limited to accelerometers, gyroscopes, pressure sensors, forcesensors, and the like. The step of providing 200 the device comprisingat least one sensor to the subject may further comprise steps of givinginstructions for the subject to properly don or apply the device. Oncethe device has been provided 200 to the subject, the next step is tomeasure the subject's external body motion 280 while the subjectperforms at least three first movement disorder tests, activities,movements or motions. Preferably, each of the at least three tests,activities, movements or motions corresponds to at least one symptom ofa movement disorder in such a way that the test, activity, movement ormotion is likely to exhibit at least one symptom of a movement disorder.Further, each of the at least three tests, activities, movements ormotions preferably corresponds to a separate symptom grouping orclassification. For example, if the tests are performed under theguidelines of the UPDRS, then each of the at least three tests wouldcorrespond to a different symptom grouping of the Motor Examinationsection (UPDRS-III), or the like. Different testing methods or protocolsmay have different groupings or classifications of symptoms, andpreferably each of the at least three tests performed correspond to adifferent grouping or classification in whichever method or protocol isused. When the subject performs the at least three tests, activities,movements or motions the at least one sensor of the device measures theexternal body motion of the subject, including any movement disordersymptom motions that are present. Either after the test is complete, orduring testing, a signal from the at least one sensor is transmitted toa processor 285. This first signal may comprise at least three separatesignals from the at least one sensor where each signal corresponds tothe measured external body motion of the at least three separate tests,activities, movements or motions, or alternatively, may be a compositesignal representing all of the measured motions as a whole. In eitherembodiment, the first signal represents the motion measured during theat least three first tests. The processor then calculates a separatesymptom quantification measure or score 290 from the first testsperformed, at least one symptom quantification measure for each separatesymptom grouping or classification. Each of the at least three separatefirst symptom quantification measures are based at least in part on thesignal received from the at least one sensor of the device correspondingto the subject's external body motion during the at least three firsttests, activities, movements or motions, and are preferably stored forlater comparison, analysis, evaluation, recollection, or other uses.Next, the at least three separate symptom quantification measures orscores are combined to calculate a first total symptom quantificationmeasure or score 295 that corresponds to the quantification of theoverall severity of the subject's movement disorder symptoms as a wholeacross all tested groupings or categories of symptoms. Each of theseparate first symptom quantification measures or scores, as well as thefirst total symptom quantification measure or score, is preferablycalculated 290, 295 substantially in real time corresponding to theperformance and/or completion of the first movement disorder test.

Subsequently, a second set of at least three movement disorder tests isperformed. Similar to the at least three first tests, the devicemeasures the subject's external body motion while the subject isperforming the at least three second tests 300. These at least threesecond tests may be performed either immediately following the firsttests, or, more preferably, at a later time (e.g., up to 30 days later),but are performed under substantially similar circumstances as the firsttests. Similarly, the second tests are preferably the same tests,activities, movements or motions as the first movement disorder tests.Again, the second signal from the at least one sensor is transmitted toa processor 305 for comparison, analysis, evaluation, recollection, orthe like. Much like the first signal, this second signal may comprise atleast three separate signals from the at least one sensor where eachsignal corresponds to the measured external body motion of the at leastthree separate tests, activities, movements or motions, oralternatively, may be a composite signal representing all of themeasured motions as a whole. In either embodiment, the second signalrepresents the motion measured during the at least three second tests.The processor similarly uses this second signal to calculate separatesecond symptom quantification measures or scores 310 from the secondtests performed, at least one symptom quantification measurecorresponding to each separate symptom grouping or classification. Eachof the at least three separate second symptom quantification measuresare based at least in part on the signal received from the at least onesensor of the device corresponding to the subject's external body motionduring the at least three second tests, activities, movements ormotions, and are preferably stored for later comparison, analysis,evaluation, recollection, or other uses. Next, the at least threeseparate second symptom quantification measures or scores are combinedto calculate a second total symptom quantification measure or score 315that corresponds to the quantification of the overall severity of thesubject's movement disorder symptoms as a whole across all testedgroupings or categories of symptoms. This process may be repeated anynumber of times, each time conducting the same movement disorder testscomprising the same tests, activities, movements or motions undersubstantially similar circumstances. The separate total symptomquantification measures or scores can then be compared in order tocalculate various sensitivity metrics corresponding to therepeatability, accuracy, consistency and the like of the device, methodand/or system. In many embodiments, the separate symptom quantificationmeasures or scores are used to measure sensitivity by calculating theintraclass correlation (ICC) 320 of the symptom quantification measures,and preferably the ICC is at least about 0.60.

FIG. 21 is a flow chart depicting the methods of several embodiments ofthe present invention for quantifying a subject's movement disordersymptoms where sensitivity is measured using minimum detectable change(MDC). First, a device comprising at least one sensor, the at least onesensor having a signal corresponding to a subject's external body motionassociated with a movement disorder, is provided 200 to the subject. Theat least one sensor may be of any variety described herein, including,but not limited to accelerometers, gyroscopes, pressure sensors, forcesensors, and the like. The step of providing 200 the device comprisingat least three sensors to the subject may further comprise steps ofgiving instructions for the subject to properly don or apply the device.Once the device has been provided 200 to the subject, the next step isto measure the subject's external body motion 245 while the subjectperforms at least two first movement disorder tests, activity, movementor motion. Preferably, each of the at least two first tests belong orcorrespond to the same symptom group of classification. For example, ifthe tests are performed under the guidelines of the UPDRS, the each ofthe at least two test would correspond to the same grouping or sectionof the UPDRS, such as the Motor Examination section (UPDRS-III), or thelike. Different testing methods or protocols may have differentgroupings or classifications of symptoms, and preferably each of the atleast two tests performed correspond to the same grouping orclassification in whichever method or protocol is used. The at least twotests, activities, movements or motions preferably corresponds to atleast one symptom of a movement disorder in such a way that the test,activity, movement or motion is likely to exhibit at least one symptomof a movement disorder. When the subject performs the at least twotests, activities, movements or motions the at least one sensor of thedevice measures 245 the external body motion of the subject, includingany movement disorder symptom motions that are present. Either after thetest is complete, or during testing, a signal from the at least onesensor is transmitted to a processor 250. The processor then calculatesa symptom quantification measure or score 255 from the at least twofirst tests performed. This first symptom quantification measure orscore is based at least in part on the signal received from the at leastone sensor of the device corresponding to the subject's external bodymotion during the at least two first tests, activities, movements ormotions, and is preferably stored for later comparison, analysis,evaluation, recollection, or other uses. The symptom quantificationmeasure or score is preferably calculated 255 substantially in real timecorresponding to the performance and/or completion of the first movementdisorder test.

Subsequently, at least two second movement disorder tests are performed.Similar to the at least two first tests, the device measures thesubject's external body motion while the subject is performing the atleast two second tests 260. The at least two second tests may beperformed either immediately following the first tests, or, morepreferably, at a later time (e.g., up to 30 days later), but areperformed under substantially similar circumstances as the first tests.Similarly, the second tests are preferably the same tests, activities,movements or motions as the first movement disorder tests. Again, thesecond signal from the at least one sensor is transmitted to a processor265 for comparison, analysis, evaluation, recollection, or the like. Theprocessor similarly uses this second signal to calculate a secondsymptom quantification measure or score 270. This process may berepeated any number of times, each time conducting the same movementdisorder tests comprising the same tests, activities, movements ormotions under substantially similar circumstances. The separate symptomquantification measures or scores can then be compared in order tocalculate various sensitivity metrics corresponding to therepeatability, accuracy, consistency and the like of the device, methodand/or system. In many embodiments, the separate symptom quantificationmeasures or scores are used to measure sensitivity by calculating theminimum detectable change (MDC) 325 of the symptom quantificationmeasures, and preferably the MDC represents at a change of about 25% orless of the total scale of the particular test(s). As noted herein, thescale and measurement units of each individual test will vary (e.g., agait test or test for standing up from a seated position may be measuredin time with a total maximum allowable time to set the scale, whereasother tests may be measured in unitless scores or different units suchas frequency, each with a different scale for maximum allowablemeasurements).

FIG. 22 is a flow chart depicting the methods of several embodiments ofthe present invention for quantifying a subject's movement disordersymptoms where sensitivity is measured using minimum detectable change(MDC). First, a device comprising at least one sensor, the at least onesensor having a signal corresponding to a subject's external body motionassociated with a movement disorder, is provided 200 to the subject. Theat least one sensor may be of any variety described herein, including,but not limited to accelerometers, gyroscopes, pressure sensors, forcesensors, and the like. The step of providing 200 the device comprisingat least one sensor to the subject may further comprise steps of givinginstructions for the subject to properly don or apply the device. Oncethe device has been provided 200 to the subject, the next step is tomeasure the subject's external body motion 280 while the subjectperforms at least three first movement disorder tests, activities,movements or motions. Preferably, each of the at least three tests,activities, movements or motions corresponds to at least one symptom ofa movement disorder in such a way that the test, activity, movement ormotion is likely to exhibit at least one symptom of a movement disorder.Further, each of the at least three tests, activities, movements ormotions preferably corresponds to a separate symptom grouping orclassification. For example, if the tests are performed under theguidelines of the UPDRS, then each of the at least three tests wouldcorrespond to a different grouping or section of the UPDRS, suchdifferent symptoms under the Motor Examination section (UPDRS-III), orthe like. Different testing methods or protocols may have differentgroupings or classifications of symptoms, and preferably each of the atleast three tests performed correspond to a different grouping orclassification in whichever method or protocol is used. When the subjectperforms the at least three tests, activities, movements or motions theat least one sensor of the device measures the external body motion ofthe subject, including any movement disorder symptom motions that arepresent. Either after the test is complete, or during testing, a signalfrom the at least one sensor is transmitted to a processor 285. Thisfirst signal may comprise at least three separate signals from the atleast one sensor where each signal corresponds to the measured externalbody motion of the at least three separate tests, activities, movementsor motions, or alternatively, may be a composite signal representing allof the measured motions as a whole. In either embodiment, the firstsignal represents the motion measured during the at least three firsttests. The processor then calculates a separate symptom quantificationmeasure or score 290 from the first tests performed, at least onesymptom quantification measure for each separate symptom grouping orclassification. Each of the at least three separate first symptomquantification measures are based at least in part on the signalreceived from the at least one sensor of the device corresponding to thesubject's external body motion during the at least three first tests,activities, movements or motions, and are preferably stored for latercomparison, analysis, evaluation, recollection, or other uses. Next, theat least three separate symptom quantification measures or scores arecombined to calculate a first total symptom quantification measure orscore 295 that corresponds to the quantification of the overall severityof the subject's movement disorder symptoms as a whole across all testedgroupings or categories of symptoms. Each of the separate first symptomquantification measures or scores, as well as the first total symptomquantification measure or score, is preferably calculated 290, 295substantially in real time corresponding to the performance and/orcompletion of the first movement disorder test.

Subsequently, a second set of at least three movement disorder tests isperformed. Similar to the at least three first tests, the devicemeasures the subject's external body motion while the subject isperforming the at least three second tests 300. These at least threesecond tests may be performed either immediately following the firsttests, or, more preferably, at a later time (e.g., up to 30 days later),but are performed under substantially similar circumstances as the firsttests. Similarly, the second tests are preferably the same tests,activities, movements or motions as the first movement disorder tests.Again, the second signal from the at least one sensor is transmitted toa processor 305 for comparison, analysis, evaluation, recollection, orthe like. Much like the first signal, this second signal may comprise atleast three separate signals from the at least one sensor where eachsignal corresponds to the measured external body motion of the at leastthree separate tests, activities, movements or motions, oralternatively, may be a composite signal representing all of themeasured motions as a whole. In either embodiment, the second signalrepresents the motion measured during the at least three second tests.The processor similarly uses this second signal to calculate separatesecond symptom quantification measures or scores 310 from the secondtests performed, at least one symptom quantification measurecorresponding to each separate symptom grouping or classification. Eachof the at least three separate second symptom quantification measuresare based at least in part on the signal received from the at least onesensor of the device corresponding to the subject's external body motionduring the at least three second tests, activities, movements ormotions, and are preferably stored for later comparison, analysis,evaluation, recollection, or other uses. Next, the at least threeseparate second symptom quantification measures or scores are combinedto calculate a second total symptom quantification measure or score 315that corresponds to the quantification of the overall severity of thesubject's movement disorder symptoms as a whole across all testedgroupings or categories of symptoms. This process may be repeated anynumber of times, each time conducting the same movement disorder testscomprising the same tests, activities, movements or motions undersubstantially similar circumstances. The separate total symptomquantification measures or scores can then be compared in order tocalculate various sensitivity metrics corresponding to therepeatability, accuracy, consistency and the like of the device, methodand/or system. In many embodiments, the separate symptom quantificationmeasures or scores are used to measure sensitivity by calculating theminimum detectable change (MDC) 330 of the symptom quantificationmeasures, and preferably the MDC represents at a change of about 25% orless of the total scale of the particular test(s). As noted herein, thescale and measurement units of each individual test will vary (e.g., agait test or test for standing up from a seated position may be measuredin time with a total maximum allowable time to set the scale, whereasother tests may be measured in unitless scores or different units suchas frequency, each with a different scale for maximum allowablemeasurements).

FIG. 23 depicts an electrical schematic block diagram of an alternativesensor unit 345 embodiment. In this embodiment, rather than using aseparate accelerometer and a separate gyroscope to measure the variousexternal body movements of the subject, a single sensor unit 345comprising at least an accelerometer and a gyroscope may be used. Thesensor unit 345 preferably not only comprises at least an accelerometer350 (denoted by the dashed box) and a gyroscope 355 (denoted by thedashed box), but also allows for integration of other sensors externalto the sensor unit 345. Preferably, the accelerometer 350 and gyroscope355 are each three-axis sensors capable of measuring their respectivemovements (acceleration and orientation) in each of the three dimensionsof movement (X, y and Z). Each of the accelerometer and gyroscope mayoutput a separate signal for their respective measurements in each axis,and these signals are all converted from analog to digital by a bank ofanalog-to-digital converters (ADC) 360. The separate ADCs for each axisof the accelerometer and gyroscope allows for simultaneous sampling ofeach sensor and eliminates the need for an external multiplexer.Preferably the sensor unit 345 as a whole, and the accelerometer andgyroscope in particular are capable of operation with low powerconsumption. Preferably, the accelerometer and gyroscope areuser-programmable such that the user may define an operating range inwhich the sensors will work (e.g., the accelerometer may be programmedto operate from as low as ±0.2 g to as high as ±16 g, and the gyroscopefrom as low as ±250 degrees/second to as high as ±2000 degrees/second).Some embodiments may include other sensors integrated into the sensorunit 345 as well, for example, a temperature sensor 365 which may beused to monitor the temperature of the sensor unit 345 and ensure it isoperating properly and under safe conditions.

The sensor unit 345 further comprises a digital motion processor (DMP)380 which may perform some preprocessing or processing of the sensorsignals using motion-related algorithms. The digital motion processor380 at least preprocesses and/or processes the accelerometer andgyroscope signals to begin the analysis of the signals and to decreasethe processing load on the external processor (not shown). Manyembodiments may include external or additional sensors (not shown) thatare not housed within the sensor unit 345, but whose signals aretransmitted to the sensor unit 345 for integration with theaccelerometer and gyroscope signals for further transmission to externalcomponents (not shown) such as a processor. Such external or additionalsensors may include, but are not limited to, force sensors,magnetometers, pressure sensors, bend sensors, combinations thereof, andthe like). These external or additional sensors communicate with thesensor unit 345 by means of an auxiliary communications interface 375.The digital motion processor can integrate the signal(s) from theseexternal or additional sensors along with the accelerometer andgyroscope signals and perform preprocessing or processing of all of thesignals together, thus further streamlining the data acquisition processand reducing the workload of the external processor (not shown).

FIG. 24 is a block diagram of the electronic components of oneembodiment of the present invention. The power receiver 400 is thecomponent which receives the electrical charge from the external powersource (not shown). The external power source can be any device forsupplying power to the subject-worn sensor unit. In some embodiments,the external power source may be a docking station to which thesubject-worn sensor unit can be connected, attached, docked, or placedinto whereby a physical connection is made between the docking stationand the subject-worn unit thus allowing power to be transferred via thephysical connection. In other embodiments, the external power source maymerely involve plugging the subject-worn sensor unit into a traditionalpower outlet. In still other embodiments, the external power source maybe an inductive charging mat or pad onto which the subject-worn sensorunit is placed and power may be inductively transferred betweeninduction coils in the charging mat or pad and the inductive coils inthe power receiver 400 of the subject-worn sensor unit, as describedherein. As the power receiver, which may be wireless or wired dependingon the embodiment, receives power, it transfers said power to a powermanager 405 which controls and directs where the incoming power isdelivered. If the subject-worn sensor unit is not being presently usedto measure a subject's body movements and is instead being charged, thenthe power manager 405 directs the incoming power to the device's batter410 for charging. It might be possible, though not necessarilypreferred, for some embodiments to allow charging while the unit isbeing used to measure a subject's body motions, in which case the powermanager 405 would direct the incoming power to either the battery 410 orto the micro-controller 420 for powering the devices operation fortesting. However, it is more preferable for the device, during operationfor testing, to be untethered and not in charging mode, and thus thebattery 410 would provide power to the unit for usage and testingpurposes.

The micro-controller 420 or microprocessor is the internal processingunit that directs the other components to function. Thus, themicro-controller 420 or microprocessor directs the power manager 405 onwhere to direct the power it is receiving from either the power receiver400 or the battery 405. The electronic clock 415 operates as commonlyknown in the art to control synchronization and operation of the deviceto maximize efficiency of power usage. The radio 425 of the devicecontrols and carries out communications between the device components,and between the subject-worn sensor unit and external devices (notshown). The radio 425 receives power directly from the power manager. Asdescribed herein, the radio may be a blue tooth communications device toprovide wireless communications with external components such ascomputers or processors, EMG signal amplifiers, data acquisitioncircuitry, internet or cloud-based memory banks or databases, and thelike, as well as internal components such as the internal subject-wornsensor unit memory 435, microprocessor 420, and the like. Both internal(between electrical components of the subject-worn sensor device) andexternal (between the subject-worn sensor device and external componentsor devices) communications may also be transmitted through wireless,wired, or a combination of both methods.

The subject-worn sensor device must, as described throughout, compriseat least one sensor 430. In the depicted embodiment, a MEMS sensor isincluded in the device. This sensor 430 may be of any of the varietiesdescribed herein or combinations thereof, though most preferablycomprises at least an accelerometer and a gyroscope. The device furthercomprises internal memory 435 which is used to store system settings aswell as subject and test data to be transmitted to external components.The micro-controller 420 comprises algorithms and protocols forcoordinating the operation of at least these internal electricalcomponents, and in some embodiments also for preprocessing or processingsensor data.

FIG. 25 is a block diagram depicting the flow of data from the devicemeasuring the subject's external body movements to the end user whoviews, analyzes and/or otherwise uses the data generated by the device.In all embodiments of the present invention, the various sensors 430 areused to measure the subject's external body motion as described herein.The sensors 430 then transmit a signal corresponding to the measuredmovements to a micro-controller or processor 420 which may perform somepre-processing or processing functions before transmitting the data tomemory or storage 440. In many embodiments, the sensors 430 andmicro-controller or processor 420 are contained in the same device 423worn by the subject. Alternatively, in many embodiments, the sensors maytransmit the data to a mobile device 433 which in turn may transmit thedata to the memory or storage 440. In such embodiments, the mobiledevice 433 may be a tablet, PC, smartphone, or the like, and may merelymake the data available to a user or may performs some processingfunctions on the data. Further alternatively, or in conjunction with theabove step, the sensor(s) 430 may directly transmit data correspondingto the subject's external body movements to the memory or storage 440.The memory or storage unit 440 may be internal to the device, though inmany embodiments is preferably an external memory or storage unit. Instill further embodiments, the memory or storage unit 440 is still morepreferably a cloud-based storage server. In most embodiments, the memoryor storage 440 preferably makes the data available to an end user 445very soon after the sensor(s) 430 record the subject's external bodymovements. The end user 445 may be a clinician who is using the data todiagnose, treat, or monitor a subject. Another potential end user may bea researcher or study administrator who is conducting a clinical trialand is collecting the data for research purposes, such as for testingthe efficacy of a drug. Other potential end users are also envisioned asusing the data, but the main goal is for the device to make the dataavailable to any authorized end user as rapidly as possible afterrecording the subject's movement. Most preferably, the data is uploadedor transmitted to the memory or storage 440 substantially simultaneouslywith recording by the sensor(s) 430, or with pre-processing orprocessing by the micro-controller or processor 420, depending on thepath and particular embodiment.

It will be apparent to those skilled in the art that variousmodifications and variations can be made to the present inventionwithout departing from the spirit and scope of the invention. Thus, itis intended that the present invention cover the modifications andvariations of this invention provided they come within the

What is claimed:
 1. A movement disorder device or system for treating asubject's Parkinson's disease through deep brain stimulation based on acalculated severity of symptoms of the subject's Parkinson's disease,the device or system comprising: a diagnostic component comprising asensor unit component and a processor, the sensor unit componentcomprising at least one external sensor having a signal for measuring asubject's external body motion or a physiological signal associated withsuch external body motion; the processor for receiving the signal andcalculating a quantified severity of the subject's symptoms ofParkinson's disease in real time; and a treatment delivery componentcomprising at least one electronic component or actuator adapted foradjusting a device for a treatment of the subject's Parkinson's diseaseor symptoms of Parkinson's disease through deep brain stimulation wherean electrical output of the deep brain stimulation is adjusted based inpart on the calculated quantified severity of the subject's symptoms ofParkinson's disease in real time, wherein the diagnostic component has areal-time average intraclass correlation (ICC) of at least about 0.60for the quantified severity of the subject's particular symptoms ofParkinson's disease.
 2. The device or system in claim 1, wherein thediagnostic component has a real-time average intraclass correlation(ICC) of at least 0.70 for the quantified severity of the subject'sparticular symptoms of Parkinson's disease.
 3. The device or system inclaim 1, wherein the device or system further comprises a displayadapted to provide instructions for the subject to perform a movementdisorder test based at least in part on an output of the diagnosticcomponent in order to quantify the severity of the subject's particularsymptoms.
 4. The device or system in claim 1, wherein further thediagnostic component has a real-time average minimum detectable change(MDC) that represents a change of about 17% or less of a total scale ofa particular rating scale of the symptom(s) when calibrated or adjusted.5. The device or system in claim 1, wherein the diagnostic component hasa real-time average intraclass correlation (ICC) of at least 0.77 forthe quantified severity of the subject's particular symptoms ofParkinson's disease.
 6. The device or system in claim 5, wherein furtherthe diagnostic component has a real-time average minimum detectablechange (MDC) that represents a change of about 17% or less of a totalscale of a particular rating scale of the symptom(s) when calibrated oradjusted.
 7. A movement disorder device or system for treating asubject's Parkinson's disease with a pharmaceutical based on acalculated severity of symptoms of the subject's Parkinson's disease,the device or system comprising: a diagnostic component comprising asensor unit component and a processor, the sensor unit componentcomprising at least one external sensor having a signal for measuring asubject's external body motion or a physiological signal associated withsuch external body motion; the processor for receiving the signal andcalculating a quantified severity of the subject's symptoms ofParkinson's disease in real time; and a treatment delivery componentcomprising at least one electronic component or actuator adapted foradjusting a device for a treatment of the subject's Parkinson's diseaseor symptoms of Parkinson's disease with a pharmaceutical where thepharmaceutical is adjusted based in part on the calculated quantifiedseverity of the subject's symptoms of Parkinson's disease in real time,wherein the diagnostic component has a real-time average intraclasscorrelation (ICC) of at least about 0.60 for the quantified severity ofthe subject's particular symptoms of Parkinson's disease.
 8. The deviceor system in claim 7, wherein the diagnostic component has a real-timeaverage intraclass correlation (ICC) of at least 0.70 for the quantifiedseverity of the subject's particular symptoms of Parkinson's disease. 9.The device or system in claim 7, wherein the device or system furthercomprises a display adapted to provide instructions for the subject toperform a movement disorder test based at least in part on an output ofthe diagnostic component in order to quantify the severity of thesubject's particular symptoms.
 10. The device or system in claim 7,wherein further the diagnostic component has a real-time average minimumdetectable change (MDC) that represents a change of about 17% or less ofa total scale of a particular rating scale of the symptom(s) whencalibrated or adjusted.
 11. The device or system in claim 7, wherein thediagnostic component has a real-time average intraclass correlation(ICC) of at least 0.77 for the quantified severity of the subject'sparticular symptoms of Parkinson's disease.
 12. The device or system inclaim 11, wherein further the diagnostic component has a real-timeaverage minimum detectable change (MDC) that represents a change ofabout 17% or less of a total scale of a particular rating scale of thesymptom(s) when calibrated or adjusted.
 13. A movement disorder deviceor system for treating a subject's Parkinson's disease with apharmaceutical or through deep brain stimulation based on a calculatedseverity of symptoms, the device or system comprising: a diagnosticcomponent comprising a sensor unit component and a processor, the sensorunit component comprising at least one external sensor having a signalfor measuring a subject's external body motion or a physiological signalassociated with such external body motion; the processor for receivingthe signal and calculating a quantified severity of the subject'sParkinson's disease symptoms in real time; and a treatment deliverycomponent comprising at least one electronic component or actuatoradapted for adjusting a device for a treatment of the subject'sParkinson's disease or symptoms of Parkinson's disease with apharmaceutical or through deep brain stimulation where thepharmaceutical or the electrical output of the deep brain stimulation isadjusted based in part on the calculated quantified severity of thesubject's symptoms of Parkinson's in real time, wherein the diagnosticcomponent has a real-time average minimum detectable change (MDC) thatrepresents a change of about 25% or less of a total scale of aparticular rating scale of the symptom(s) when calibrated or adjusted.14. The device or system in claim 13, wherein the diagnostic componentfurther has a real-time average intraclass correlation (ICC) of at least0.60 for the quantified severity of the subject's particular symptoms ofParkinson's disease.
 15. The device or system in claim 13, wherein thediagnostic component further has a real-time average intraclasscorrelation (ICC) of at least 0.70 for the quantified severity of thesubject's particular symptoms of Parkinson's disease.
 16. The device orsystem in claim 13, wherein the diagnostic component further has areal-time average intraclass correlation (ICC) of at least 0.77 for thequantified severity of the subject's particular symptoms of Parkinson'sdisease.
 17. The device or system in claim 13, wherein the diagnosticcomponent has a real-time average minimum detectable change (MDC) thatrepresents a change of about 17% or less of a total scale of aparticular rating scale of the symptom(s) when calibrated or adjusted.18. The device or system in claim 17, wherein the diagnostic componentfurther has a real-time average intraclass correlation (ICC) of at least0.60 for the quantified severity of the subject's particular symptoms ofParkinson's disease.
 19. The device or system in claim 17, wherein thediagnostic component further has a real-time average intraclasscorrelation (ICC) of at least 0.70 for the quantified severity of thesubject's particular symptoms of Parkinson's disease.
 20. The device orsystem in claim 17, wherein the diagnostic component further has areal-time average intraclass correlation (ICC) of at least 0.77 for thequantified severity of the subject's particular symptoms of Parkinson'sdisease.